| WUSS |
2026 |
A Structured Agent-Based Framework for Early-Stage Data Science Pipelines |
Dheerusha Tiwari,
Siddharth Birajdar |
source |
14 |
| WUSS |
2026 |
Building Better Data Science Workflows: Best Practices with Git, GitHub, Data Version Control (DVC), and MLflow for Open-Source Collaboration |
Ryan Paul Lafler |
source |
15 |
| WUSS |
2026 |
Demystifying Regression Analysis Techniques with R |
Zheyuan Yu,
Kirk Paul Lafler,
Zichun Gao,
Jiaxin Xu,
Zeqi Li,
Ruochen Shao |
|
35 |
| WUSS |
2026 |
Enhancing Your SAS Viya Workflows with Python: Integrating Python's Open-Source Libraries with SAS using PROC PYTHON |
Ryan Paul Lafler,
Miguel Bravo Martinez del Valle |
source |
12 |
| WUSS |
2026 |
Generations of SAS Analytics: Perspectives from Baby Boomers, Generation X, Millennials, and Generation Z on the Future of SAS, AI, and Data Science [presentation] |
Mike Krizan,
Stephen B. Sloan,
Kirk Paul Lafler,
Ryan Paul Lafler,
Lida Gharibvand |
source |
6 |
| WUSS |
2026 |
SQL Everywhere! Reuse your PROC SQL Code in R and Python with DuckDB |
Matthew T. Slaughter,
Isaiah Lankham,
Kirk Paul Lafler |
source |
19 |
| PharmaSUG CN |
2026 |
A Dual-Harness Workflow to Wrap AI into Observable, Reusable Clinical Table Delivery: From SAP Intent to Shell-Aligned Execution |
Wenjun Zhu |
source |
14 |
| PharmaSUG CN |
2026 |
AI-Native Real-Time SDTM Mapping and Exploration Agent |
Hao Chen,
Xuejie Zhou,
Haomin Yang,
Qianwang Wang |
source |
13 |
| PharmaSUG CN |
2026 |
Automating ADaM Specification with AI: Intelligent Generation, Risk Assessment, and Human-in-the-Loop Review |
Shuang Gao,
Yaohui Zhu,
Tingting Zeng,
Jinling Li,
Wei Wang |
source |
11 |
| PharmaSUG CN |
2026 |
ClaudeAgentSDK and shinyAssistantUI: Extending Claude Code's AI Agent Capabilities to the R Ecosystem |
Kaiping Yang,
Jie Liu |
source |
12 |
| PharmaSUG CN |
2026 |
Efficient Strategies for Handling Data Issues in Clinical Trial Submissions |
Kate Sun |
source |
7 |
| PharmaSUG CN |
2026 |
From SAP to TFL: An AI-Assisted Workflow Framework for Automated Shells and TFLs |
Xiaoyu Ding,
Guoqing Zhao,
Huafeng Gao,
Zhiyuan Guo |
source |
18 |
| PharmaSUG CN |
2026 |
Handling Missing Data in Analgesia Clinical Trials and Corresponding SAS Implementation |
Jingbo Zhu,
Jiehan Zhang |
source |
17 |
| PharmaSUG CN |
2026 |
Safety Estimands and Analysis Dataset Design: Advancing Safety Evaluation in Clinical Trials |
Kun Ren,
Zeyu Guang |
source |
11 |
| PharmaSUG |
2026 |
AI-Assisted Modular Design for R Markdown Report Generation A Hybrid Architecture for Enhanced Maintainability and Cross-Study Scalability |
Song Liu,
Jingwei Xiong |
source |
13 |
| PharmaSUG |
2026 |
AI-Driven Intelligent Platforms for ADaM Specification and Code: Empowering Clinical Data Analysis |
Tingting Zeng,
Jia He,
Yaohui Zhu,
Shuang Gao,
Jinling Li,
Nana Yang |
source |
11 |
| PharmaSUG |
2026 |
Algorithms to align the distribution of follow-up across independently collected cohorts when comparing time to event endpoints using conventional Kaplan Meier and Cox regression methods. |
Shankar Srinivasan,
Yvonne Buttkewitz,
Regina Uttenreuther,
Baldeep Chani Talwar,
Manjari Dissanayake |
source |
12 |
| PharmaSUG |
2026 |
An Agentic AI Framework That Reads Statistical Analysis Plans and Generates TFL Table of Contents |
Siqi Wang,
Toshio Kimura,
Songgu Xie,
Weiming Du |
source |
6 |
| PharmaSUG |
2026 |
An End-to-End R-Based Pharmacokinetics (PK) Workflow for Regulatory Submission: The INAVO120 Study |
Qi Liu,
Shweta Vadhavkar |
source |
5 |
| PharmaSUG |
2026 |
Analysis Concepts role within the CDISC 360i vision |
Alyssa M. Wittle,
Brian Harris |
source |
5 |
| PharmaSUG |
2026 |
Assessing Quality of Real-World Data Sources |
S. Robert Collins |
source |
4 |
| PharmaSUG |
2026 |
Beyond Today-s Evidence: How AI-Enabled RWE Will Transform Development Speed, Study Quality, and Real-World Impact |
Sherrine Eid |
source |
15 |
| PharmaSUG |
2026 |
Beyond WHODrug: Insight into Concomitant Medication Data Analysis |
Song Liu,
Martin Nielsen,
Rambabu Sura |
source |
9 |
| PharmaSUG |
2026 |
Bridging the Gap: Table-Driven SAS Programming as a Pathway to AI in Clinical Trials Statistical Programming |
James Sun,
Vijaya Nadella,
Daniel Qi |
source |
15 |
| PharmaSUG |
2026 |
Building Better Data Science Workflows: Best Practices with Git, GitHub, and Data Version Control (DVC) for Effective Collaboration |
Ryan Paul Lafler |
source |
17 |
| PharmaSUG |
2026 |
Current Review of Open Source in New Drug Applications: R & Python |
Philip Bowsher |
source |
3 |
| PharmaSUG |
2026 |
Embracing Novel Approaches to Automated Causal Inference Framework |
Laura Watson,
Sherrine Eid |
source |
15 |
| PharmaSUG |
2026 |
Enhancing Your SAS Viya Workflows with Python: Integrating Python's Open-Source Libraries with SAS using PROC PYTHON |
Ryan Paul Lafler,
Miguel Bravo Martinez del Valle |
source |
13 |
| PharmaSUG |
2026 |
Evaluation of Azure OpenAI ChatGPT API as Code Assistance Tools for Statistical Programming in SAS, R and Python. |
Ajay Gupta,
Misikir Tesfaye |
source |
25 |
| PharmaSUG |
2026 |
Friction to Flow: LLM-Based Automation of Clinical Data Workflows |
Pankaj Attri,
Matthew J. Becker |
source |
8 |
| PharmaSUG |
2026 |
From Automation to Evidence: Governing LLMs and AI Agents in Real-World Outcomes Research |
Sherrine Eid |
source |
17 |
| PharmaSUG |
2026 |
From Exploratory Data Analysis to Machine Learning: Continuing My Python Journey |
Leon Rod Davoody |
source |
13 |
| PharmaSUG |
2026 |
From SAP to CSR: A Metadata-Driven TFL Workflow |
Bhavin Busa |
source |
7 |
| PharmaSUG |
2026 |
Has your SAS being 'MEAN' to your data yet? |
Ruth Marisol Rivera Barragan,
Isaac Vazquez |
source |
8 |
| PharmaSUG |
2026 |
Implementing AI Agent-Driven Tools to Accelerate Clinical Research Workflows |
Nathan Lee |
source |
13 |
| PharmaSUG |
2026 |
Insights and Experience Sharing with Patient-Reported Outcome Data Analysis in FDA-s Submission |
Jingyuan Chen |
source |
8 |
| PharmaSUG |
2026 |
Investigator-Initiated Trials: Navigating Statistical Programming Challenges with Practical Solutions |
Vikas Patil,
Ramesh Sundaram |
source |
6 |
| PharmaSUG |
2026 |
It-s a Wonderful Lifecycle: Translating Statistical Programming into Modern Analytics Development |
Steve Nicholas |
source |
3 |
| PharmaSUG |
2026 |
Keynote Presentation: Between Hype and Reality: Posit's Blueprint for Responsible GenAI in Life Sciences [presentation] |
Tareef Kawaf |
source |
28 |
| PharmaSUG |
2026 |
Leveraging LLMs in Data Science Web Applications: Beyond the Chat Interface |
Tyler Rowsell,
Nandini Thampi,
Dishank Jani,
Hao Xu |
source |
18 |
| PharmaSUG |
2026 |
Managing Unblinded Activities Internally: The Independent Statistical Analysis Team (iSAT) Model |
Hong Wang,
Shu Chen,
Chen Li |
source |
4 |
| PharmaSUG |
2026 |
Navigating Career Transitions: From Programmer to Executive Leader |
Steven Tan |
source |
7 |
| PharmaSUG |
2026 |
Oncology Solid Tumor Subcutaneous vs Intravenous Late-stage Study Analysis |
Sumanjali Mangalarapu,
Chuqing Chen,
Anilkumar Anksapur |
source |
11 |
| PharmaSUG |
2026 |
Operationalizing Generative AI in Regulated Analytics: Applied Implementation Patterns for Enterprise Deployment |
Lida Gharibvand |
source |
16 |
| PharmaSUG |
2026 |
R Package Management in LSAF: Challenges and Solutions |
Praneeth Adidela,
Sagar Koona |
source |
7 |
| PharmaSUG |
2026 |
Regression Analysis Made Easy Using R |
Zheyuan Yu,
Kirk Paul Lafler,
Zichun Gao,
Jiaxin Xu,
Zeqi Li,
Ruochen Shao |
source |
32 |
| PharmaSUG |
2026 |
Smarter, Faster, Better: GenAI-Driven Authoring for Data Reviewer's Guides |
Christina Scienski,
Christine Rossin |
source |
4 |
| PharmaSUG |
2026 |
Structure-Preserving Preprocessing of Clinical Documents for Large Language Model Analysis |
Zun Wang,
Juntao Yan |
source |
12 |
| PharmaSUG |
2026 |
Swimmer Plots - Some Practical Advice |
Ilya Krivelevich |
source |
11 |
| PharmaSUG |
2026 |
Ten Rules for Better Charts, Figures and Visuals |
Kirk Paul Lafler |
source |
19 |
| PharmaSUG |
2026 |
Women Leadership in AI-Driven Clinical Programming: Navigating Intersectionality and Innovation |
Lida Gharibvand |
source |
31 |
| PHUSE US |
2026 |
A Practical Approach to Causal Inference |
Sherrine Eid,
Laura Watson |
source
presentation source |
10 |
| PHUSE US |
2026 |
Accelerating Study Insights: Agile Data Visualisation Using R-Shiny |
Lin Yuan,
Heather Howell |
source
presentation source |
6 |
| PHUSE US |
2026 |
Acquiring a Compound with Multiple Clinical Trials? Let's Get Ready for a Type C Meeting! Key Considerations for Preparing Its Regulatory Submission |
Mathura P. Ramanathan,
Kajal Tahiliani |
source
presentation source |
12 |
| PHUSE US |
2026 |
Advancing Precision Medicine and Regulatory Readiness: Data Harmonisation and Statistical Methods for Companion Diagnostics Bridging Studies |
Ummul Vara Qurratul Ain |
source
presentation source |
10 |
| PHUSE US |
2026 |
AI Code Generator: Automating TFL Programming with ARS Metadata |
Bhavin Busa,
Navin Dedhia |
source
presentation source |
5 |
| PHUSE US |
2026 |
AI Reading and Understanding the SAP to Generate the TFL TOC |
Siqi Wang,
Toshio Kimura |
source
presentation source |
6 |
| PHUSE US |
2026 |
AI-powered approach for faster, more efficient authoring of clinical and regulatory documents |
Abhijeet Arora |
source
presentation source |
4 |
| PHUSE US |
2026 |
An AI-Driven Framework for Automated Statistical Analysis Plan Generation in Clinical Trials |
Qingyuan Zhang |
source
presentation source |
8 |
| PHUSE US |
2026 |
Analysis Concepts Definition: Initial Perspectives from the CDISC Working Group |
Stuart Malcolm |
source
presentation source |
4 |
| PHUSE US |
2026 |
Around the Data DOSE-y Doe: Using DOSExx Variables within ADaM Datasets |
Inka Leprince,
Richann J. Watson |
source |
10 |
| PHUSE US |
2026 |
Breaking into Statistical Programming: How SAS, R, Python, AI and ML Are Shaping Career Paths |
Kishore Pothuri |
source
presentation source |
6 |
| PHUSE US |
2026 |
Bridging Analysis and Strategy: The Transformative Role of Statistical Analysts in Drug Development |
Lingsong Yun |
source
presentation source |
17 |
| PHUSE US |
2026 |
Challenges and Solutions for Generating Synthetic CDISC Data |
Sundaresh Sankaran,
Catherine Briggs |
source
presentation source |
6 |
| PHUSE US |
2026 |
Consistency, Speed and Satisfaction: The Impact of TLF Mock Shell Centralisation |
Jie Yang |
source
presentation source |
6 |
| PHUSE US |
2026 |
Data Harmonisation for ISS and ISE: A Practical Checklist for Integration Success |
Qiong Wei,
Lily Cheng |
source
presentation source |
10 |
| PHUSE US |
2026 |
Design of Everyday Shiny Apps |
Maya Gans,
Casey Aguilar-Gervase |
source |
5 |
| PHUSE US |
2026 |
DevOps for Clinical Data Science: A Leap into the Future of Clinical Analysis |
Frikkie Oppel,
Riaan Van Straaten |
source
presentation source |
6 |
| PHUSE US |
2026 |
Ensuring Reliability of Medical Devices Through Statistical Oversight in the Age of AI |
Parvee Kumar,
Shrutimita Pokhariyal |
source
presentation source |
11 |
| PHUSE US |
2026 |
Framework for Incorporating Estimands within the Statistical Analysis Plan |
Inderjeet Arora |
source
presentation source |
9 |
| PHUSE US |
2026 |
From SAS to R for TLGs: A Case Study on Implementing an 'R-First, SAS-QC' Workflow for Time-to-Event Analysis |
Adler Moisés Fallas Rodríguez |
source
presentation source |
8 |
| PHUSE US |
2026 |
Handle with Care: Study-Specific Assessment of R Package Risk |
Shannon Grant |
source
presentation source |
9 |
| PHUSE US |
2026 |
Influence Without Authority: Leadership Lessons for Statistical Programmers |
Steven Tan |
source
presentation source |
8 |
| PHUSE US |
2026 |
Interactive and Instant: GenAI-Driven Creation of Clinical Trial Applications |
Marcin Dubel |
source
presentation source |
12 |
| PHUSE US |
2026 |
Is the AI Coding Assistant Catching Your Vibe? A Practical Assessment of Generative AI Tools in Clinical Data Analytics |
Chendi Liao |
source
presentation source |
6 |
| PHUSE US |
2026 |
Manual vs AI-Assisted Workflows: Practical Strategies for Complex R Package Development [presentation] |
Vedha Viyash |
source |
41 |
| PHUSE US |
2026 |
Maximising Longevity and Saving Costs Through Refactoring of Statistical Computing Environments |
Srinath Viswanathan,
Vaithi Bharath |
source
presentation source |
7 |
| PHUSE US |
2026 |
Next Generation QC Workflow Optimisation: Current Practices and Future Directions from the Emerging Trends & Innovation Working Group |
Matthew Finnemeyer,
Caroline Phares |
source
presentation source |
13 |
| PHUSE US |
2026 |
Opening Session - Global Data Sharing Platforms: Aligning Frameworks, Pressures and Opportunities [presentation] |
Cathal Gallagher |
source |
31 |
| PHUSE US |
2026 |
Perspective on Enterprise AI and Posit Tooling |
Philip Bowsher |
source
presentation source |
22 |
| PHUSE US |
2026 |
Problem-First Agentic AI: Transforming Statistical Computing with Purposeful Automation |
Rajesh Hagalwadi |
source
presentation source |
8 |
| PHUSE US |
2026 |
Prompt Engineering in Gen AI: A Game Changer for the professional development of Statistical Programmers and Data Scientists |
Kevin Lee |
source
presentation source |
8 |
| PHUSE US |
2026 |
Revolutionising Clinical Data Transformation: Harnessing GenAI and Open Source for Automated SDTM Conversion |
Hao (Harry) Chen,
Jian Hua Hang |
source
presentation source |
6 |
| PHUSE US |
2026 |
Strategic Approaches to Patient Centricity in Data Science [presentation] |
Sylvia Baedorf Kassis |
source |
21 |
| PHUSE US |
2026 |
The Clinical Data Lake: Empowering the Data Caterer Vision with Veeva, SAS and Open Source |
Sascha Ahrweiler,
Holger Dach |
source
presentation source |
7 |
| PHUSE US |
2026 |
Transforming Legacy Data into CDISC Standards: Practical Approaches and Regulatory Insights |
Khalif Halani,
Veena Palle |
source
presentation source |
6 |
| PHUSE US |
2026 |
What Pharma Can Learn from Data Science Outside the Industry |
Kris Wenzel,
Liz Cole |
source
presentation source |
11 |
| PHUSE US |
2026 |
Your Next Teammate Has Arrived: Our Story & Reflections on Building AI Coding Assistant for Clinical Insights Generation |
Vincent Shen |
source
presentation source |
4 |
| PHUSE APAC |
2026 |
Accelerating Productivity: Understand How SAS Viya Copilot Helps Users Work More Effectively Across the Analytics Life Cycle |
Ajay Tomar |
source
presentation source |
6 |
| PHUSE APAC |
2026 |
Accelerating Regulatory Submissions with R: A Scalable and Compliant Approach |
Priyanka Sawant |
source
presentation source |
6 |
| PHUSE APAC |
2026 |
Advancing Clinical Trial Analysis with Trimmed Means: Estimands, Intercurrent Events, and Regulatory Alignment |
Prasanth Palanisamy |
source
presentation source |
9 |
| PHUSE APAC |
2026 |
AI-Driven Protocol Review: Accelerating and Simplifying Review |
Aditya Moogi |
source
poster source |
14 |
| PHUSE APAC |
2026 |
An AI-Powered Digital Standards Library for Accelerated Regulatory Submissions |
Anshu Aman,
Varun Sethuraman |
source
presentation source |
4 |
| PHUSE APAC |
2026 |
Annualized Relapse Rate and Clinical Profiles in South Korean Multiple Sclerosis Patients: A Sample Cohort Study Using Korean National Health Insurance Data |
Seongjun Byun,
Jisuk Jo |
source
presentation source |
8 |
| PHUSE APAC |
2026 |
aRe You Ready!! Fun, Fast & Functional Coding Tips |
Xeviers Koner |
source
presentation source |
4 |
| PHUSE APAC |
2026 |
Beyond Code: Elevating NextGen Statistical Programmers through Cross-Functional Learnings |
Saumil Tripathi |
source
presentation source |
7 |
| PHUSE APAC |
2026 |
Bridging Statistical Expertise Through Intuitive Design: A Modern Web Interface for Automated SAS Procedure Selection in Cardiovascular Clinical Trials |
Likith Gopikumar |
source
presentation source |
10 |
| PHUSE APAC |
2026 |
Cross-Platform Programming for Clinical Development: Practical Use of SAS, R, and Python |
Sandeep Lakkol,
Vinay S |
source
presentation source |
7 |
| PHUSE APAC |
2026 |
Development of Statistical Scientists for Pharmaceutical Drug Development at India Global Capability Centres |
Suresh Chenji |
source
presentation source |
6 |
| PHUSE APAC |
2026 |
E2E Clinical Metadata Journey: 'Single Source of Truth' to Accelerate Clinical Research - From Collection and Tabulation to Analysis and Reporting |
Indumathi Narasetty |
source
presentation source |
9 |
| PHUSE APAC |
2026 |
Estimands Framework Through the Eye of a Statistical Programmer |
Shraddha Ganoo,
Kinjal Pandat |
source
presentation source |
9 |
| PHUSE APAC |
2026 |
External Comparator Studies in the Era of Real-World Data |
Vishal Goriya,
Anshul Sinha,
Gerd Rippin |
source
presentation source |
5 |
| PHUSE APAC |
2026 |
From Data to Digital Phenotypes: Modelling High-Dimensional PROs and Actigraphy Data in Decentralized Psychiatric Trials |
Sakshi Kaushik |
source
presentation source |
14 |
| PHUSE APAC |
2026 |
From Static to Interactive: A Comparative Evaluation of ggplot2 and Plotly in Clinical Data Visualisation |
Mugdha Joshi |
source
presentation source |
8 |
| PHUSE APAC |
2026 |
From Uncertainty to Clarity: A Personal Journey in Pharma Data Science Using the Johari Window |
Ratna Kumari Koganti,
Ramya Pichikala |
source
presentation source |
7 |
| PHUSE APAC |
2026 |
Future-Focused Real-World Data Use Strategies: Resilience and Innovation at Chugai |
Wataru Ohtsuka,
Nauta Yamanaka |
source
presentation source |
8 |
| PHUSE APAC |
2026 |
Harnessing Quarto’s Multi-Language Framework: Integrating Analytical Rigour with Interactive Visualisation for Enhanced Clinical Insights |
Alvin Pitchaiah,
Venkata Manoj Yellamilli |
source
presentation source |
3 |
| PHUSE APAC |
2026 |
Optimising Few-Shot Prompting Strategies for Scalable and Reliable Enterprise AI Applications |
Varun Sethuraman,
Avinash Patnaik |
source
presentation source |
10 |
| PHUSE APAC |
2026 |
Standardization of Auxiliary Medicinal Products (AxMPs) in Clinical Trials |
Divya Mekala,
Manoj Mishra |
source
presentation source |
3 |
| PHUSE APAC |
2026 |
Streamlining Python and R Code Generation from SAP and Programming Specifications Using Multi-Agent LLMs |
Siju Chacko,
Abhishek Mishra |
source
presentation source |
8 |
| PHUSE APAC |
2026 |
The Intelligence Shift in AI Driven Clinical Trials [presentation] |
Sanjeev Sachdeva |
source |
11 |
| PHUSE APAC |
2026 |
Unlock Deeper Clinical Insights: A Unified Approach to Data Analysis with SAS, R, and Python |
Pavan Kallurkar |
source
presentation source |
7 |
| PHUSE APAC |
2026 |
Unlocking Biopharma Insights: A RAG-Enabled AI Framework for Rapid Access to Clinical and Nonclinical Study Data |
Lakshmi B K,
Sapna Chandran |
source
presentation source |
9 |
| PHUSE APAC |
2026 |
Unveiling Powerful Patient Data Insights Through Graph Database |
Sonal Dedhia |
source
presentation source |
10 |
| PHUSE APAC |
2026 |
ValoRpacks - self-service R package validation |
Marc Jantke |
source
presentation source |
5 |
| PHUSE EU |
2025 |
%CallR |
Duong Tran |
source
poster source |
14 |
| PHUSE EU |
2025 |
A Code Assistant for Clinical Trial Tables |
Pietro Mascheroni,
Torben Brehme |
source
poster source |
6 |
| PHUSE EU |
2025 |
ADaM Conformance Rules: Bridging the Gap Between Standards and Practice |
Rafik Ghazaryan |
source
presentation source |
6 |
| PHUSE EU |
2025 |
AI Chatbot in an SCE |
Shivoy Pandita,
Marc Jantke |
source
presentation source |
8 |
| PHUSE EU |
2025 |
Aspirations of language agnosticism - experiences expanding the programming stack with python |
Kaj Arai Hejlesen,
Michael Svingel |
source
presentation source |
9 |
| PHUSE EU |
2025 |
Becoming an Independent Consultant And Stepping into the Fourth Dimension |
Jean-Marc Ferran |
source
presentation source |
6 |
| PHUSE EU |
2025 |
Beyond the Code: Evolving from Clinical Programmer to Strategic Partner in Clinical Trials |
Anastasiia Khoba |
source
presentation source |
4 |
| PHUSE EU |
2025 |
Blinded & Coordinated: Aligning People and Processes To Prevent Unblinding |
Monika Bajek,
Dubravka Georgijevic |
source
presentation source |
6 |
| PHUSE EU |
2025 |
Bridging Languages: Building Integrated Analytical Tools with SAS, R, and Python for Clinical Data |
Margarethe Povey |
source
presentation source |
7 |
| PHUSE EU |
2025 |
Bridging the Gap: Translating Intercurrent Events into Analysis-Ready ADaM Datasets |
Meghna Diedrich |
source
poster source |
9 |
| PHUSE EU |
2025 |
Contributions to CAMIS PHUSE Project in 2025: Tobit Regression, Reference-based Multiple Imputation and Tipping Point Analysis |
Yannick Vandendijck |
source
presentation source |
12 |
| PHUSE EU |
2025 |
Decode Your Future: A Professional Development Growth Map for Programmers and Statisticians by Role Type |
Diana Stuart |
source
poster source |
8 |
| PHUSE EU |
2025 |
Detecting Logical Errors in Clinical Programming by Applying ChatGPT |
Illia Skliar |
source
presentation source |
9 |
| PHUSE EU |
2025 |
Digital SAP Model Using Biomedical Concepts |
Tom Ratford |
source
presentation source |
5 |
| PHUSE EU |
2025 |
Diversity, Inclusion and Equality Its Just Good Science! |
Roxanne McGuire,
Chris Ward |
source
presentation source |
19 |
| PHUSE EU |
2025 |
Efficient Conversion of SDTM/ADaM Specifications from Excel to Define-XML v2.1 Using Pinnacle 21 Community |
Hiromi Okada,
Seiko Yamazaki |
source
presentation source |
15 |
| PHUSE EU |
2025 |
End-to-End R: Where To Start? |
Luke Thompson |
source
presentation source |
6 |
| PHUSE EU |
2025 |
FAIRchive Cloud-Based and GxP-Compliant Long-Term Archiving for Clinical Trial Data |
Frank Stoinski,
Alexander Lüders |
source
presentation source |
10 |
| PHUSE EU |
2025 |
From Overload to Insight: Personal Knowledge Management for Clinical Data Scientists in the Age of Generative AI |
Sascha Ahrweiler |
source
presentation source |
9 |
| PHUSE EU |
2025 |
From Static Archives to Analytical Intelligence: Transforming Statistical Analysis Value Through Standardization |
Ilan Carmeli |
source
presentation source |
8 |
| PHUSE EU |
2025 |
From Statistical Programming to AI Automation in Data Management: A Cross-Departmental Tech Journey |
Irene Luna,
Marcia Vaz |
source
presentation source |
5 |
| PHUSE EU |
2025 |
How to map lab data into the LB domain and ADLB |
Bert Parmet |
source
poster source |
6 |
| PHUSE EU |
2025 |
IDD'AI: Automating the Tedious So You Can Focus on the Genius |
Lionel Debecq,
Samantha Cambier |
source
presentation source |
8 |
| PHUSE EU |
2025 |
Interactive Insights: Leveraging R Shiny for Enhanced Data Visualisation in Clinical Trial Readouts [presentation] |
Carolyn Fisher,
Elisabeth Deutschmann |
source |
20 |
| PHUSE EU |
2025 |
Landing Moonshots |
Ross Farrugia |
source
presentation source |
8 |
| PHUSE EU |
2025 |
Leveraging AI for Seamless SAS to R Migration: Challenges and Opportunities |
Milena Kraus,
Corrina Stoeckinger |
source
presentation source |
11 |
| PHUSE EU |
2025 |
Leveraging LLM for R Shiny App Code Development: A Case Study with Event Prediction [presentation] |
Yirong Cao |
source |
15 |
| PHUSE EU |
2025 |
Modernising Clinical Data Science: Best Practices for a Unified, Governed SCE [presentation] |
Matthew Tendler |
source |
13 |
| PHUSE EU |
2025 |
Multiple Imputations Overview of Missing Data Problem, Solution Methods and SAS Implementation |
Dmytro Kalinin |
source
presentation source |
13 |
| PHUSE EU |
2025 |
On the Right Track: Managing Platform Modular Studies with a Central Metadata Switchboard |
Dubravka Georgijevic,
Carla Santillán |
source
presentation source |
7 |
| PHUSE EU |
2025 |
Pharmacokinetics Is Simple... Sometimes |
Vincent Buchheit |
source
presentation source |
12 |
| PHUSE EU |
2025 |
Qualitative ADaM Datasets and Define-XML Without Using ADaM Specs |
Pieter Coppens |
source
presentation source |
4 |
| PHUSE EU |
2025 |
R Adoption and Change Management A Large CRO Perspective |
Martin Brown,
Lynn Clipstone |
source
presentation source |
8 |
| PHUSE EU |
2025 |
R-Burst: The User Support Approach Shaping GSK's Open-Source Strategy |
Andy Nicholls |
source
presentation source |
5 |
| PHUSE EU |
2025 |
SAIL.R: Navigating Change Together in Clinical Analytics! |
Annemie Van Dijck |
source
presentation source |
11 |
| PHUSE EU |
2025 |
SAMBA: Bridging the Gap How GenAI Transforms Analysis Plans into ADaM Specs [presentation] |
Thiago Figueiredo,
Richard Becker |
source |
19 |
| PHUSE EU |
2025 |
Statistical Endpoints and Analysis in Diagnostic Imaging: The Matrix Has You and Your Data |
Srinivas Lanka,
James Sykes |
source
presentation source |
17 |
| PHUSE EU |
2025 |
Survival analysis for AdVerse events with VarYing follow-up times (SAVVY)-estimation of adverse event risks |
Regina Stegherr,
Claudia Schmoor,
Jan Beyersmann,
Kaspar Rufibach,
Valentine Jehl,
Andreas Brückner,
Lewin Eisele,
Thomas Künzel,
Katrin Kupas,
Frank Langer,
Friedhelm Leverkus,
Anja Loos,
Christiane Norenberg,
Florian Voss,
Tim Friede |
source
poster source |
13 |
| PHUSE EU |
2025 |
Talk to Your Data: Accelerating Insights with AI-Powered Dashboards |
Emily Yates |
source
presentation source |
8 |
| PHUSE EU |
2025 |
The Art of Timely Deliverables: How We Learned To Stop Worrying and Love the Deadline |
Søren Fjelstrup |
source
presentation source |
12 |
| PHUSE EU |
2025 |
The Chicken, the Egg and the ADaM: Cracking the PRE-ADSL vs ADSL Sequence |
Carla Santillán,
Dubravka Georgijevic |
source
presentation source |
8 |
| PHUSE EU |
2025 |
The Human Element: Synergising Emotional and Physical Intelligence in Statistical Programming Leadership |
Harris Kampouris,
Lino Jardim |
source
presentation source |
12 |
| PHUSE EU |
2025 |
The Power of Early Careers: Investing in the Next Generation |
Miles Almond,
Jun Se Kim |
source |
13 |
| PHUSE EU |
2025 |
The Value of Clinical Trial Data: From Submission to Innovation |
Anne Katrine Alsing |
source
presentation source |
8 |
| PHUSE EU |
2025 |
Turbocharge Your Trials: Transform CRF Creation and the CDISC standardization process with Xbiom's Smart Metadata Repository and AI/ML Integrations |
Harinarayanan Gopichandran |
source
presentation source |
8 |
| PHUSE EU |
2025 |
Turning Data into Deliverables: Automating Biometrics from Metadata to TFLs |
Inderjeet Arora |
source
presentation source |
9 |
| PHUSE EU |
2025 |
Twice as Much Aint Twice as Good: Is Double Programming Really the Gold Standard We Think it Is? |
Vitali Gering |
source
presentation source |
6 |
| PHUSE EU |
2025 |
Unlocking Efficiency Through Digitisation: Plotting the Journey with Atlas for Clinical Trial Output Generation [presentation] |
Daphné Grasselly,
Eddy Foster |
source |
20 |
| PHUSE EU |
2025 |
Unlocking Healthcare Insights: Graph-Based Modelling and Analysis of Synthetic Patient Data |
George Panagiotakis,
Nikolaos Kountouris |
source
presentation source |
18 |
| PHUSE EU |
2025 |
Validated Statistical Computing: A Kubernetes Framework for Regulatory-Compliant R, Python and SAS Deployments |
T. Randall Betancourt,
Tim Fantuzzo |
source
presentation source |
53 |
| PHUSE EU |
2025 |
What a Good One Looks Like Building a Team of Internal R Experts [presentation] |
Mike Smith |
source |
24 |
| PHUSE EU |
2025 |
Why Wait for Real Data? The Power of Synthetic Data in Modern Clinical Trials |
Abhijeet Arora |
source
presentation source |
6 |
| MWSUG |
2025 |
Advancing Research in Rare Disease Using SAS Viya [presentation] |
Kelly Olano,
Pierce Kuhnell,
Laurie Smith |
source |
18 |
| MWSUG |
2025 |
Benefits, Challenges, and Opportunities with Open Source Technologies in the 21st Century |
Kirk Paul Lafler,
Ryan Paul Lafler,
Joshua J. Cook,
Stephen B. Sloan,
Anna T. K. Wade |
source |
8 |
| MWSUG |
2025 |
Conducting Survival Analysis in SAS using Medicare Claims as a Real-world data source |
Jayanth Iyengar |
source |
32 |
| MWSUG |
2025 |
Data Literacy 101: Understanding Data and the Extraction of Insights |
Kirk Paul Lafler |
source |
9 |
| MWSUG |
2025 |
Prompt, Program, Submit: Generative AI for Faster SDTM, ADaM, and TLFs |
Matthew J. Becker,
Pankaj Attri |
source |
7 |
| SESUG |
2025 |
AP Statistics and SaS |
Immanuel Pulavarti |
|
8 |
| SESUG |
2025 |
Best Practices for Graphic Design & Color Use, Plus Uncommon Data Art for Data Science |
LeRoy Bessler |
|
108 |
| SESUG |
2025 |
Comparing analysis method implementations in software (CAMIS) |
Brian K. Varney |
|
4 |
| SESUG |
2025 |
The Business Value of Diversity Combined with Data Science |
Stephen B. Sloan |
|
5 |
| WUSS |
2025 |
Around the Data DOSE-y Doe, How Much Fun Can Your Data Can Be: Using DOSExx Variables within ADaM Data Sets |
Inka Leprince,
Richann J. Watson |
source |
13 |
| WUSS |
2025 |
Conducting Survival Analysis in SAS using Medicare Claims as a Real-world data source |
Jayanth Iyengar |
source |
32 |
| WUSS |
2025 |
Evolving Human Emotions Under a Global Crisis: An Analysis of Popular Music Sentiment |
Hamed Hemmati,
Bennett Frohock |
source |
23 |
| WUSS |
2025 |
Monetize Your SAS Insights |
Karen Walker |
source |
9 |
| WUSS |
2025 |
Prompt, Program, Submit: Generative AI for Faster SDTM, ADaM, and TLFs |
Matthew J. Becker |
source |
7 |
| PharmaSUG |
2025 |
A Customizable Framework in R for Presenting BICR Data in a User-Friendly Format |
Reneta Hermiz,
Jing Ji |
source |
14 |
| PharmaSUG |
2025 |
A Quick Start Guide to Writing a Technical or Research Paper |
Kirk Paul Lafler |
source |
10 |
| PharmaSUG |
2025 |
Accelerating Data Discovery and Governance: Unlocking Insights with Metadata Management, Data Catalogs, and LLM Integration for Streamlined Regulatory Approval in Clinical Trials |
Pritesh Desai,
Samiul Haque |
source |
7 |
| PharmaSUG |
2025 |
Addressing Challenges in Real-World Evidence Generation: The AI-SAS for Real-World Evidence Approach |
Takuji Komeda,
Yuki Yoshida,
Yohei Komatsu,
Yoshitake Kitanishi |
source |
7 |
| PharmaSUG |
2025 |
Addressing early challenges in RWD data standardization for analysis and reporting of RWE studies |
Xingshu Zhu,
Li Ma,
Bo Zheng |
source |
9 |
| PharmaSUG |
2025 |
AI Empowered Metadata Governance |
Prasoon Sangwan |
source |
9 |
| PharmaSUG |
2025 |
AI is coming for you: New Biometric Leadership in the era of Gen AI |
Kevin Lee |
source |
7 |
| PharmaSUG |
2025 |
AI Performing Statistical Analysis: A Major Breakthrough in Clinical Trial Data Analysis |
Toshio Kimura,
Siqi Wang,
Weiming Du,
Songgu Xie |
source |
11 |
| PharmaSUG |
2025 |
An End-to-End Workflow for TFL Generation using R: MMRM Applications and Comparative Insights with SAS |
Kai Lei,
Jiaqiang Zhu,
Margaret Huang |
source |
14 |
| PharmaSUG |
2025 |
An Introduction to the Role of Statistical Programming in Medical Affairs |
Nagadip Rao |
source |
9 |
| PharmaSUG |
2025 |
Association of Alzheimer-s Disease with Cardiovascular Disease and Depression in Older Adults: Findings from the 2018 Nationwide Inpatient Sample |
Prayag Shah |
source |
27 |
| PharmaSUG |
2025 |
Automated Word Report Generation for Standardized CMC PC Study with Programmatically Inserted Contents in R |
Song Liu,
Jiannan Kang |
source |
16 |
| PharmaSUG |
2025 |
BDS Dataset with PARQUAL and PARQTYP Variables for Time-to-Safety Events Analysis |
Kang Xie |
source |
9 |
| PharmaSUG |
2025 |
Benefits, Challenges, and Opportunities with Open Source Technologies in the 21st Century |
Kirk Paul Lafler,
Ryan Paul Lafler,
Joshua J. Cook,
Stephen B. Sloan,
Anna T. K. Wade |
source |
7 |
| PharmaSUG |
2025 |
Bridging the Gap: Leadership of Statistical Programmers in Clinical Trials |
Allison Covucci,
Xiaohan Zou |
source |
6 |
| PharmaSUG |
2025 |
Building Extensible Python Classes for Analysis and Research : It-s Easier Than You Think! |
Sundaresh Sankaran,
Samiul Haque |
source |
8 |
| PharmaSUG |
2025 |
Building Resilient Teams |
Patrick Grimes,
Sajin Johnny |
source |
15 |
| PharmaSUG |
2025 |
Checking SDTM Datasets from Biostatistical Perspective |
Inka Leprince,
Elizabeth Li |
source |
14 |
| PharmaSUG |
2025 |
Clopper Pearson CI? get your data ready for it! |
Ruth Marisol Rivera Barragan,
Isaac Vazquez |
source |
7 |
| PharmaSUG |
2025 |
Comparing SAS and R Approaches in Reshaping data |
Yachen Wang,
Chen Ling |
source |
12 |
| PharmaSUG |
2025 |
Comparing SQL and Graph Database Query Methods for Answering Clinical Trial Questions with LLM-Powered Pipelines |
Jaime Yan |
source |
24 |
| PharmaSUG |
2025 |
Conducting Survival Analysis in SAS using Medicare Claims as a Real-world data source |
Jayanth Iyengar |
source |
32 |
| PharmaSUG |
2025 |
Data management and biostatistics synergy: how to achieve and what can be expected |
Diana Avetisian |
source |
11 |
| PharmaSUG |
2025 |
Debugging Options in R: Applications and Usage in Clinical Programming |
Madhusudhan Ginnaram,
Bingjun Wang,
Jeetender Chauhan,
Sarad Nepal |
source |
6 |
| PharmaSUG |
2025 |
Deciphering Exposure-Response Analysis Datasets: A Programmer-s Perspective for Oncology Studies |
Sabarinath Sundaram |
source |
6 |
| PharmaSUG |
2025 |
Decoding the Role of Statistical Programming - A Decade of Keytruda Submissions and Approvals |
Mary N. Varughese,
Hong Qi |
source |
8 |
| PharmaSUG |
2025 |
Efficient Strategies for Handling Data Issues in Clinical Trial Submissions |
Kate Sun |
source |
7 |
| PharmaSUG |
2025 |
Enhance Safety Data Analysis Using SafetyGraphic R Package |
Vicky Yuan |
source |
17 |
| PharmaSUG |
2025 |
Generative AI in Biometrics: Transforming Clinical Trials with Supercharged Efficiency an Innovation |
Kevin Lee |
source |
6 |
| PharmaSUG |
2025 |
Handling Health Regulatory Information Requests: Best Practices and Strategies |
Himanshu Patel,
Chintan Pandya |
source |
11 |
| PharmaSUG |
2025 |
Harnessing AI & CDISC ARS for Effortless Statistical Reporting & CSR Writing |
Bhavin Busa,
Navin Dedhia |
source |
10 |
| PharmaSUG |
2025 |
Integrating Generative AI into Medical Writing: Building an Interactive Drafting and Search Framework |
Tadashi Matsuno |
source |
12 |
| PharmaSUG |
2025 |
Interactive Longitudinal Data Analysis and Visualization in Clinical Research Using R. |
María José Gómez Ramírez |
source |
8 |
| PharmaSUG |
2025 |
Leveraging Python for Statistical Analysis in Public Health: Techniques and Visualizations for Life Sciences Professionals |
Michael Carnival |
source |
14 |
| PharmaSUG |
2025 |
Mastering the Maze of Oncology Endpoints: A Unified SAS Approach for Randomized Controlled Trial Analysis |
Yuxin Wang,
Kelly Chao,
Wenqing Yu,
Hongbing Jin |
source |
11 |
| PharmaSUG |
2025 |
Multiple Imputation Techniques in the Context of ADaM Datasets |
Shunbing Zhao,
Linping Li |
source |
11 |
| PharmaSUG |
2025 |
Name That ADaM Dataset Structure |
Nancy Brucken |
source |
8 |
| PharmaSUG |
2025 |
Optimizing SAS Programming Pipelines Using the %Unpack and %SearchReplace Macros for Version Control and Customization |
Ning Ning,
Assir Abushouk |
source |
8 |
| PharmaSUG |
2025 |
Our Second Brain: A Guide to Building Note System for SAS Programmer in Clinical Trial |
Zeyu Li |
source |
5 |
| PharmaSUG |
2025 |
Programming Perspectives for Efficient and Accurate C-QTc Analysis |
Lingjie Zhang,
Lata Maganti,
Richard Moreton,
Runcheng Li |
source |
11 |
| PharmaSUG |
2025 |
Python with Hermione: Unleash Your Inner Coding Witch & Dragon |
Charu Shankar,
Jim Box |
source |
20 |
| PharmaSUG |
2025 |
Rising Above Artificial Intelligence: Feeling Confident With Your Human Intelligence |
Priscilla Gathoni |
source |
15 |
| PharmaSUG |
2025 |
The Current State of Teaching Biostatistics in Academia: Challenges and Software Solutions |
Lida Gharibvand |
source |
5 |
| PharmaSUG |
2025 |
The Winding Road to ADSL |
Elizabeth Dennis,
Grace Fawcett |
source |
6 |
| PharmaSUG |
2025 |
Time-to-Deterioration for Patients Reported Outcomes |
Christine S Teng |
source |
11 |
| PharmaSUG |
2025 |
Traceability and AI for Improved Understanding, Communication and QC of Clinical Trials |
Tomás Sabat Stofsel |
source |
5 |
| PharmaSUG |
2025 |
Trying Out Positron: New IDE for Statistical Programming |
Philip Bowsher |
source |
10 |
| PharmaSUG |
2025 |
Unlocking Success: Lessons from Building R-Based Statistical Packages in Pharma |
Sydney Hyde,
Yirong Cao |
source |
9 |
| PharmaSUG |
2025 |
Updating Define-XML packages: Tips and A Comprehensive Checklist |
Qiong Wei,
Ji Qi,
Lixin Gao |
source |
10 |
| PharmaSUG |
2025 |
Visualizing oncology data through 3D bar charts in R and Python |
Girish Kankipati,
Venkatesulu Salla |
source |
18 |
| PharmaSUG |
2025 |
Which ADaM Data Structure Is Most Appropriate? Gray Areas in BDS and OCCDS. |
Veronica Gonzalez |
source |
15 |
| PHUSE US |
2025 |
A Journey Through an Innovative Approach to Migration of Legacy System to New Multilingual Statistical Computing Environment (SCE) |
Kajal Tahiliani |
source
presentation source |
9 |
| PHUSE US |
2025 |
Actual Intelligence and Artificial Intelligence Joining Forces to Perform Statistical Analysis, Turning AI Hype into Reality |
Songgu Xie,
Toshio Kimura |
source
presentation source |
11 |
| PHUSE US |
2025 |
Advancing Safety Evaluation in Oncology Trials Using Estimands |
Reshma Radhakrishnan,
Lakshmi Mantha |
source
presentation source |
8 |
| PHUSE US |
2025 |
Applied Strategy: The Human Touch to Success |
Shereen Anisa Khwajazada |
source
presentation source |
3 |
| PHUSE US |
2025 |
Automating SAS and R Code Interpretation and Debugging: A Practical Pipeline for Statistical Programmers |
Tingting Tian,
Jaime Yan |
source
presentation source |
13 |
| PHUSE US |
2025 |
Building Rome in a Few Months: How Open-Source Technologies Empower Small Pharma |
Chendi Liao,
Kasra Yousefi |
source
presentation source |
5 |
| PHUSE US |
2025 |
Changes to the Job of a Statistical Programmer in the Pharmaceutical Industry |
James J. Kim |
source
presentation source |
8 |
| PHUSE US |
2025 |
Clinical Trial Reporting Automation Based on Knowledge Graph |
Jaya Simha Inampudi |
source
poster source |
5 |
| PHUSE US |
2025 |
Data Transformation: Achieving Compliance with Irregular Data |
Reyes Eduardo Elizalde Duarte |
source
presentation source |
6 |
| PHUSE US |
2025 |
Demystifying the Handling and Mapping of External Data to CDISC Standards in Clinical Trials |
Murali Kanakenahalli,
Vamsi Kandimalla |
source
presentation source |
12 |
| PHUSE US |
2025 |
E2E R Submission from a Roche Oncology Study |
Jingyuan Chen,
Hinal Patel |
source
presentation source |
6 |
| PHUSE US |
2025 |
Efficient TFL Review within Statistical Programming - Using R and SAS |
Siddharth Kumar |
source
presentation source |
8 |
| PHUSE US |
2025 |
Enhancing Clinical Trial Data Queries with LLMs and Neo4j: A Flexible Framework for ADaM Dataset Management |
Jaime Yan |
source
presentation source |
28 |
| PHUSE US |
2025 |
Enhancing the (ASAP) Aggregate Safety Assessment Planning Framework with an Interactive R Markdown Application: Seeing is believing! |
Debopriya Ghosh |
source
presentation source |
7 |
| PHUSE US |
2025 |
eProtocol and the Promise of Automation |
Bill Qubeck,
Suhas Giriraj |
source
presentation source |
17 |
| PHUSE US |
2025 |
Evaluation of Open-Source Technologies in Clinical Trial Reporting |
Jaimin Patel |
source
poster source |
7 |
| PHUSE US |
2025 |
From Data Manager to Data Scientist: Navigating the Future of Data Management in Clinical Trials |
Debra Anderson |
source
presentation source |
6 |
| PHUSE US |
2025 |
From Fragmentation to Fusion: A Journey through Mergers and Acquisitions Data Integration Challenges |
Xiao Huang |
source
presentation source |
3 |
| PHUSE US |
2025 |
From Manual to Machine: Leveraging Best-of-Breed Approaches in Clinical Data Management |
Joseph Lebers |
source
presentation source |
10 |
| PHUSE US |
2025 |
Gen-AI for Statistical Reporting and Clinical Study Report (CSR) Writing |
Leveraging CDISC |
source
presentation source |
10 |
| PHUSE US |
2025 |
GPT-Powered Data Insights: Advancing Clinical Data Analytics with Large Language Models (LLMs) |
Melanie Hullings |
source
presentation source |
5 |
| PHUSE US |
2025 |
Harnessing Analysis Results Datasets (ARDs) for Clinical Reporting in R: Our First ARD-Based Filing Experience |
Daniel Sjoberg,
Nolan Steed |
source |
6 |
| PHUSE US |
2025 |
Harnessing the Power of R Shiny in a GxP-Compliant and Validated Manner for Clinical Trial Use |
Sanyogeeta Andhale,
Shilpa Sood |
source
presentation source |
13 |
| PHUSE US |
2025 |
Health Authority Interactions and Communication During the Submission Process |
Ritesh Dhimmar,
Raman Bassi |
source
presentation source |
5 |
| PHUSE US |
2025 |
How Unique is it for the Subject Identifier in a Study To Have Multiple Screenings and Enrolments? |
Anahita Vyas,
Rama Kudaravalli |
source
presentation source |
8 |
| PHUSE US |
2025 |
Integrating Gen AI with an Open-Source Toolkit for Clinical Insight Generation to Boost Data Science Efficiency |
Vincent Shen |
source
presentation source |
3 |
| PHUSE US |
2025 |
Integration of AI with R Studio: Advantages and Disadvantages |
Mahesh Minnakanti,
Karthikrao Perala |
source
presentation source |
8 |
| PHUSE US |
2025 |
Kraken: A Shiny Application for Visualising SDTM Data in Early-Phase Clinical Trials |
Rutu Patel |
source
presentation source |
12 |
| PHUSE US |
2025 |
Leadership Presentations: How and Why, Statistical Programming Leaders Need to Plan for Next Generation Statistical Programming [presentation] |
Francis Kendall |
source |
29 |
| PHUSE US |
2025 |
Leadership Presentations: Turning Disruption into Opportunity - Guiding Teams Through AI-Powered Transformation [presentation] |
Li Zheng |
source |
20 |
| PHUSE US |
2025 |
Learning by Doing: Empowering Professional Growth Through Collaborative Python Automation |
Azadeh Gilanpour,
Vanessa Chavez |
source
presentation source |
11 |
| PHUSE US |
2025 |
Let's Talk Future: Automated Solution for Standard-Compliant Data, Mock Shells and TFL Generation Using Open-Source Platforms with AI |
Inderjeet Arora,
Abhijeet Arora |
source
presentation source |
8 |
| PHUSE US |
2025 |
Leveraging NLP for Clinical Trial Efficiency: Development of a Protocol-Aware AI Chatbot |
Seamus Gallivan,
Sairam Tangirala |
source
presentation source |
8 |
| PHUSE US |
2025 |
LLMs in Clinical Trials: Overcoming Challenges Related to Patient Confidentiality and Intellectual Property |
Amit Javkhedkar,
Samip Shah |
source
presentation source |
7 |
| PHUSE US |
2025 |
Metaprogramming in R |
Sudhir Kedare,
Rajprakash Chennamaneni |
source
presentation source |
5 |
| PHUSE US |
2025 |
Navigating the Complexities of AESI: A Centralised Approach to Molecule-Level Management |
Tian Fang,
Xiaojing Zhu |
source
presentation source |
7 |
| PHUSE US |
2025 |
Optimising Leadership Strategies for Global Teams Through Time Zone-Based Task Assignment |
Tigran Alikhanyan,
Erik Torosyan |
source
presentation source |
7 |
| PHUSE US |
2025 |
Optimising SDTM and ADaM: Remediation Techniques for Data Accuracy |
Kishore Pothuri |
source
presentation source |
10 |
| PHUSE US |
2025 |
Optimizing Development and Regulatory Submission of eSUB Package for Exposure-Response and PK/PD Analysis |
Saumilkumar Tripathi,
Ephicacy Lifescience |
source
presentation source |
10 |
| PHUSE US |
2025 |
Pivoting to AI: Turning Career Transition into Innovation |
Rick Stephens,
Good Gorilla |
source
poster source |
5 |
| PHUSE US |
2025 |
Positron: Overview for Pharma |
Philip Bowsher,
Cole Arendt |
source
presentation source |
18 |
| PHUSE US |
2025 |
Practical Evaluation of AutoML Platforms for Clinical Data Science |
Shubhranshu Dutta |
source
poster source |
4 |
| PHUSE US |
2025 |
Real-World Data - Analysis-Ready Datasets: A Standardised, Specialised and Innovative Data Solution for Efficient Real-World Data Analysis |
Nayan Chaudhary,
Navdeep Pal |
source
presentation source |
12 |
| PHUSE US |
2025 |
Regulatory Submissions - Exciting, Challenging, or Both? |
Ganeshchandra Gupta,
Randi McFarland |
source
presentation source |
5 |
| PHUSE US |
2025 |
Revolutionising Clinical Trials: Gen AI-Powered Biometrics Breakthroughs |
Kevin Lee |
source
presentation source |
6 |
| PHUSE US |
2025 |
Scaling up: accelerating self-hosted open-access LLMs to compete with the Big Three (ChatGPT, Claude, Gemini) |
Kostiantyn Drach |
source
presentation source |
12 |
| PHUSE US |
2025 |
Streamlining Machine Learning Modelling in Neuroscience Clinical Trials Through Cross-Functional Collaboration |
Jing Dai |
source
presentation source |
5 |
| PHUSE US |
2025 |
Surviving a Sunset: Being Resilient in the Face of Open-Source Disruption |
Franklin E. Menius |
source
presentation source |
5 |
| PHUSE US |
2025 |
The Development of the CDISC eTFL Portal To Support the Adoption and Implementation of the Analysis Result Standard |
Bess LeRoy,
Bhavin Busa |
source
presentation source |
8 |
| PHUSE US |
2025 |
The Implementation of {teal} Shiny Apps for DMC Activities |
Zhen Wu,
Peng Zhang |
source
presentation source |
7 |
| PHUSE US |
2025 |
The R Test Kitchen: Cooking Up Quality in Clinical Analytics & Reporting |
Emily Yates |
source
presentation source |
6 |
| PHUSE US |
2025 |
Topline Considerations for Double-Blind Trials |
Veena Palle,
Naresh Gopalkrishna |
source
poster source |
5 |
| PHUSE US |
2025 |
Transforming Clinical Trials with AI-Driven Protocol Optimization and Next-Gen Statistical Programming |
Ravindra Shukla |
source
presentation source |
8 |
| PHUSE US |
2025 |
Transforming Clinical Trials: Leveraging Bayesian Statistics in Innovative Trial Design, Analysis, Applications and Navigating Challenges |
Jaskaran Singh Saini |
source
presentation source |
11 |
| PHUSE US |
2025 |
Turbocharge Your Trials: Transform CRF Creation and the CDISC standardization process with Xbiom's Smart Metadata Repository and AI/ML Integrations |
Harinarayanan Gopichandran |
source
presentation source |
8 |
| PHUSE US |
2025 |
Unleashing the Power of {teal}: New Features and Cross-Industry Collaboration |
Nina Qi,
Dony Unardi |
source
presentation source |
6 |
| PHUSE US |
2025 |
Unlocking the Secrets of Health: A Unified Approach to Biomarker and Clinical Data Integration |
Pavan Kumar Tatikonda |
source
presentation source |
8 |
| PHUSE US |
2025 |
Validated by Verisian: The Future of Quality Control and Validation in Clinical Trial Analyses |
Henning Kuich |
source
presentation source |
12 |
| PHUSE US |
2025 |
Wearable Technology: Enhancing Patient Monitoring and Real-World Evidence |
Bill Qubeck,
Sridhar Vijendra |
source
presentation source |
15 |
| PHUSE US |
2025 |
Why Be Different? Shouldn't Everyone Be Using Agile to Deliver Their Clinical Trials? |
Michael S Rimler |
source
presentation source |
5 |
| MWSUG |
2024 |
Being A Statistical Expert Witness [presentation] |
David J. Corliss |
source |
21 |
| MWSUG |
2024 |
Charting Your Organization's Machine Learning Roadmap |
Ryan Paul Lafler |
source |
7 |
| MWSUG |
2024 |
Data Literacy 101: Understanding Data and Extracting Insights |
Kirk Paul Lafler |
source |
9 |
| MWSUG |
2024 |
Evaluating Internal Consistency of Questionnaire Data |
Yida Bao,
Zheng Zhang,
Jiafeng Ye,
Liangliang Xu,
Tao Jiang,
Yongli Zhao,
Philippe Gaillard |
source |
15 |
| MWSUG |
2024 |
Making Text Analytics More Approachable: From Traditional to Generative AI for Business Applications [presentation] |
Vikranth Reddy Chapaala |
source |
13 |
| MWSUG |
2024 |
Predicting the Impact of Storms on Utility Customers [presentation] |
David J. Corliss |
source |
23 |
| MWSUG |
2024 |
SAS PROC GEOCODE By Example: A Case Study [presentation] |
Louise S. Hadden |
source |
44 |
| MWSUG |
2024 |
The Business Value of Diversity Combined with Data Science [presentation] |
Stephen B. Sloan |
source |
14 |
| PHUSE EU |
2024 |
Accelerating GSK's Open-Source Journey with The AI Programmer |
Andy Nicholls,
UK Christina Fillmore |
source
presentation source |
7 |
| PHUSE EU |
2024 |
An Experiment on the Use of Altair SLC for Clinical Study Analytics |
Mark Holland,
Michael Byrne |
source
presentation source |
9 |
| PHUSE EU |
2024 |
Artificial Intelligence Potential Use Cases in Clinical Data Engineering |
Deepak Pakalapati,
Mounika Pillamarapu |
source
presentation source |
8 |
| PHUSE EU |
2024 |
Auto-Generating the List of Tables from a Statistical Analysis Plan - A Case Study [presentation] |
Jaya Simha Inampudi,
Krishna Gopal |
source |
14 |
| PHUSE EU |
2024 |
Automating Real-World Data Analysis Using R Packages and Shiny: A Three-Stage Workflow |
Stavros Oikonomou,
Louise Raiteri |
source
presentation source |
8 |
| PHUSE EU |
2024 |
Back to the Drawing Board - Accelerating RShiny Application Development with Effective User Interface Designs |
Barbara Mikulasova |
source
poster source |
4 |
| PHUSE EU |
2024 |
Block by Block: introducing blockr, the Flexible Open-Source Dashboard Builder |
Karma Tarap,
Jean-Philippe Coene |
source
presentation source |
7 |
| PHUSE EU |
2024 |
Bridging Platforms: Integrating RStudio POSIT and SAS Grid into the Same Environment |
Sebastià Barceló |
source
poster source |
5 |
| PHUSE EU |
2024 |
Bridging Statistical Programming and Data Management: A Job Rotation Experience |
Frederikke Høyer |
source |
4 |
| PHUSE EU |
2024 |
Bridging the Gap: Role Transition from SAS Programmer to Data Scientist |
Mrityunjay Kumar,
Shashikant Kumar |
source
presentation source |
7 |
| PHUSE EU |
2024 |
Connecting Standard from Design to Analysis to Submission: Finishing the CDISC 360 Vision [presentation] |
Peter Van Reusel |
source |
25 |
| PHUSE EU |
2024 |
Developing Validated R Packages for Standardised and Efficient Statistical Report Generation at Roche Diagnostics |
Dorothee Childs,
Christoph Ehret |
source
presentation source |
9 |
| PHUSE EU |
2024 |
Estimands: How to Make ADaM Implementation Your Friend |
Jaclyn Amberg |
source
presentation source |
10 |
| PHUSE EU |
2024 |
Exploring the Strengths and Challenges of Neurodiversity Within the Pharmaceutical Industry |
Melis Blackford |
source
poster source |
2 |
| PHUSE EU |
2024 |
Four Languages, Three Years: An Agile Approach to Data Science [presentation] |
Shannon Haughton |
source |
11 |
| PHUSE EU |
2024 |
Generative AI: A Clinical Programmer's Friend! |
Karl Kennedy,
Daniel Ghali |
source
presentation source |
10 |
| PHUSE EU |
2024 |
How to Optimise Your SAS Code: Tips and Tricks |
Vismaya Kondassam Veedu |
source
presentation source |
16 |
| PHUSE EU |
2024 |
Interactive Session - The State of Open Source Technology in Clinical Data Analysis, Reporting, and Submissions - A PHUSE Manuscript [presentation] |
Katja Glass,
Michael S Rimler |
source |
27 |
| PHUSE EU |
2024 |
Keynote Speaker - Maneesh Juneja [presentation] |
Maneesh Juneja |
source |
104 |
| PHUSE EU |
2024 |
Leveraging 'Ensemble' Machine Learning Models to Drive Automation of Specification Generation and Data Mapping in Clinical Trial Data Submission |
Venu Mallarapu |
source
presentation source |
10 |
| PHUSE EU |
2024 |
Leveraging Data Science and Analytics to Optimise Clinical Trial Execution |
Melanie Hullings |
source
presentation source |
4 |
| PHUSE EU |
2024 |
Leveraging Shiny Modules for Modular and Scalable Web Applications for Clinical Trials/Research |
Sohan Lal,
Pinku Hooda |
source
presentation source |
10 |
| PHUSE EU |
2024 |
Navigating First Data Submission: Pierre Fabre's Journey and Insights into Data Submission Challenges with the NMPA |
Romain Raymond,
Benoit Sansas |
source
presentation source |
7 |
| PHUSE EU |
2024 |
Navigating Personal and Continuing Professional Development - A Journey into Data Science |
Jawan Thapa |
source
poster source |
2 |
| PHUSE EU |
2024 |
Navigating the Data Storm: Strategic Mastery for Sustaining Technical Excellence Amid Industry Shifts |
Mahdi About |
source
presentation source |
8 |
| PHUSE EU |
2024 |
Quality Tolerance Limits: Understanding the added value and statistical need of implementing QTLs to assure subject safety and data quality |
Nathalie van Borrendam |
source
presentation source |
3 |
| PHUSE EU |
2024 |
R Evolution: A Guide for Training SAS Programmers |
Michael Walshe |
source
presentation source |
10 |
| PHUSE EU |
2024 |
Return On Investment as a Financial Feng-Shui in Data Science. Practical Strategies to Get Projects Accepted and Evaluated |
Iwona Matyjaszek |
source
presentation source |
2 |
| PHUSE EU |
2024 |
Revolutionising Statistical Programming Activities - StatProg CoPilot Consortium Leveraging on Open-Source World and Generative AI |
Sébastien Tourlet |
source
presentation source |
4 |
| PHUSE EU |
2024 |
SAIL.R: A Journey Towards R Software at Johnson & Johnson - A Training Perspective |
Yannick Vandendijck |
source
presentation source |
10 |
| PHUSE EU |
2024 |
SAS Custom Step & R-Runner: Develop any application you can dream about |
Olivier Bouchard |
source
presentation source |
12 |
| PHUSE EU |
2024 |
SCE Alchemy: The Return of the QC Process, and Rise of Training via LLM |
Steve Griffiths,
Eleanor Sparling |
source
presentation source |
6 |
| PHUSE EU |
2024 |
Serverless Shiny - Evolving Landscape of Clinical Analytics |
Philip Bowsher,
George Stagg |
source
presentation source |
5 |
| PHUSE EU |
2024 |
Stop Chatting, Start Scanning: AI's Visual Takeover in Pharma for Data Extraction with the Power of LLMs |
Ercan Suekuer |
source
presentation source |
3 |
| PHUSE EU |
2024 |
Strategies to Improve Understanding of Estimands and Analysis Section of Statistical Analysis Plan |
Inderjeet Arora |
source
presentation source |
8 |
| PHUSE EU |
2024 |
The Development of the CDISC eTFL Portal to Support the Adoption and Implementation of the Analysis Results Standard |
Bess LeRoy,
Bhavin Busa |
source
presentation source |
8 |
| PHUSE EU |
2024 |
The Magical Trinity of TLF Automation: Digital Documents, Metadata, and GenAI |
Alastair Scarlett |
source
presentation source |
4 |
| PHUSE EU |
2024 |
The Open SCE: A Call to Action One Year Later |
Caroline Phares,
Pascal Bouquet |
source
presentation source |
6 |
| PHUSE EU |
2024 |
The R Journey to Submission |
Hinal Patel,
Welwyn Garden |
source
presentation source |
6 |
| PHUSE EU |
2024 |
The TransCelerate/CDISC Digital Data Flow Project: Practical Electronic Study Designs [presentation] |
David Iberson-Hurst |
source |
8 |
| PHUSE EU |
2024 |
Tips and Tricks: From Specification to Define.xml v2.1 using SAS |
Caroline Pelckmans |
source
presentation source |
18 |
| PHUSE EU |
2024 |
Transcriptomics - A Demanding Data Analysis that Expands the Limits of Regulated Clinical Data Handling |
Lea Yoshida Hildebrandt |
source
presentation source |
6 |
| PHUSE EU |
2024 |
Transparent ggplot2: Enhancing Reproducibility with ggcall |
Maciej Nasinski |
source
presentation source |
6 |
| PHUSE EU |
2024 |
Unveiling the Tipping Point: An In-depth Analysis |
Varsha Mithun Patil,
Ephicacy Lifescience |
source
presentation source |
8 |
| PHUSE EU |
2024 |
Using Git and GitLab to Empower QC Workflow and Project Management in Clinical Reporting |
Kieran Martin,
Welwyn Garden |
source
presentation source |
5 |
| PHUSE EU |
2024 |
Where Does Your SCE Fit in Your Data Strategy? |
Phil Loucks |
source
presentation source |
7 |
| PHUSE EU |
2024 |
Working with Omics data - A Statistical Programmers perspective |
Adrian Czaban |
source
presentation source |
10 |
| SESUG |
2024 |
Applying Different Data Cutoff Dates for the Analysis of a Study Milestone |
Guowei Zhao,
Hong Qi |
source |
7 |
| SESUG |
2024 |
Benefits, Challenges, and Opportunities with SAS and Open-Source Software (OSS) Integration |
Kirk Paul Lafler,
Ryan Paul Lafler,
Stephen B. Sloan,
Joshua J. Cook |
source |
7 |
| SESUG |
2024 |
Charting Your Organization's Machine Learning Roadmap |
Ryan Paul Lafler |
source |
7 |
| SESUG |
2024 |
Data Literacy 101: Understanding Data and the Extraction of Insights |
Kirk Paul Lafler |
source |
9 |
| SESUG |
2024 |
SAS and Python can complement each other in statistical modeling |
Valentina Grouverman,
Lindzee Smith |
source |
5 |
| SESUG |
2024 |
Ten Rules for Better Charts, Figures and Visuals |
Kirk Paul Lafler |
source |
19 |
| SESUG |
2024 |
The Dreaded Data Type Conversion, Character to Numeric, Numeric to Character, a Deep Dive. |
Emily F. Zucker |
source |
12 |
| SESUG |
2024 |
The Essentials Given - Becoming an Expert of Statistical Programming in Pharma & Health Care Industry |
Hongbo Li |
source |
5 |
| SESUG |
2024 |
Unveiling the Diagnostic Potential of Radiomics-Based PET and CT Imaging through Statistical and Machine Learning Techniques |
Mostafa Zahed,
Janet Kireta,
Victor Aderanti,
Maryam Skafyan |
source |
21 |
| SESUG |
2024 |
Using Data Visualization to Explore the Association Between Education and Mortality: Insights from the 2012-2018 National Health Interview Survey Linked Mortality Files |
Cindy Zhang,
Jessie Parker,
Yeats Ye,
Cordell Golden |
source |
25 |
| SESUG |
2024 |
Using SAS and R to Create Plot for Temperature Study |
Abbas S. Tavakoli,
Isabelle Bennett,
Robin B. Dail |
source |
10 |
| WUSS |
2024 |
An introduction to Quarto: A Versatile Open-Source Tool for Data Reporting and Visualization |
Joshua J. Cook,
Swann Arp Adams |
source |
18 |
| WUSS |
2024 |
Benefits, Challenges, and Opportunities with SAS and Open-Source Software (OSS) Integration [presentation] |
Kirk Paul Lafler,
Ryan Paul Lafler,
Joshua J. Cook,
Stephen B. Sloan,
Anna T. K. Wade |
source |
33 |
| WUSS |
2024 |
Charting Your Organization's Machine Learning Roadmap |
Ryan Paul Lafler |
source |
6 |
| WUSS |
2024 |
Correlation of a Composite Self-Reported Symptoms Severity Score with Patient Number of Symptoms as Predictors of SARS-CoV-2 infection status/Viral Load using the SAS System [presentation] |
Jesse Albert Canchola,
Daniel Jarem,
Alison Kuchta |
source |
54 |
| WUSS |
2024 |
Customizing SAS Studio in Viya - The Next Step [presentation] |
Danny R. Modlin |
source |
5 |
| WUSS |
2024 |
Get a GPS to Navigate Your Skills to Find Career Purpose [presentation] |
Lisa A. Mendez,
Charu Shankar |
source |
11 |
| WUSS |
2024 |
iCSR: A Wormhole to Interactive Data Exploration Universe |
Sudhir Kedare,
Steve Wade |
source |
7 |
| WUSS |
2024 |
SAS Visual Analytics a low code no code approach to dashboard reporting [presentation] |
Charu Shankar |
source |
56 |
| WUSS |
2024 |
SAS Viya in Action: Enhancing Life Sciences Data Analysis [presentation] |
Matthew J. Becker |
source |
13 |
| WUSS |
2024 |
The Business Value of Diversity Combined with Data Science |
Stephen B. Sloan |
source |
5 |
| WUSS |
2024 |
The Current State of Teaching Biostatistics in Academia [presentation] |
Lida Gharibvand |
source |
14 |
| WUSS |
2024 |
Training Domain Specific AI for Clinical Data: Developing an AI Agent to Transform EDC Data to CDISC SDTM and then to ADaM Standards |
Sy J. Truong |
source |
12 |
| WUSS |
2024 |
Will statistical programmers be replaced by Artificial Intelligence? [presentation] |
Junying Zhang |
source |
20 |
| PharmaSUG CN |
2024 |
Application of I&I Late Phase in Programming |
Renxiang Wang |
source |
15 |
| PharmaSUG CN |
2024 |
Compare and batch validation in R for mixed QC |
Perphy Zhao,
Melody Yu,
Michael Wang,
Qian Su |
source |
13 |
| PharmaSUG CN |
2024 |
E9(R1) Program Practice and Its Application in Sensitivity Analysis |
Dawei Jiao |
source |
6 |
| PharmaSUG CN |
2024 |
Enhancing Patient Profile Visualization through Clustering Algorithms: An Exploration of Smart Data Presentation Techniques |
Zhengyuan Wen,
Kang Zhao |
source |
8 |
| PharmaSUG CN |
2024 |
General Considerations for Integrating ADaM Data and Special Handling of One Complex Case in ISS |
Niandong Yang |
source |
7 |
| PharmaSUG CN |
2024 |
Graph Programming Tips for Swimmer Plot |
Xin Jiang,
Wenyi Yu |
source |
5 |
| PharmaSUG CN |
2024 |
Implementation on concentration-QTc modeling |
Daoqing Li,
Deli Cao |
source |
20 |
| PharmaSUG CN |
2024 |
Implementing Statistical Methods in Companion Diagnostic: A Case Study in NSCLC |
Danxia Hu,
Mandy Gao,
Jianyong Tong |
source |
10 |
| PharmaSUG CN |
2024 |
Interactive Presentation with Python Streamlit |
Wei (Tony) Zhang |
source |
7 |
| PharmaSUG CN |
2024 |
LiveTFL -- A Centralized Clinical Analysis Platform Based on the Teal Framework and Enhanced by AI |
Kaiping Yang,
Jie Liu,
Cheng Zhang,
Yuhang Liu |
source |
22 |
| PharmaSUG CN |
2024 |
Programming Perspective: Streamline Estimands, Strategies, and Design ADaM for Estimand |
Yuqin Wu |
source |
10 |
| PharmaSUG CN |
2024 |
Trial Agent: An Innovative and Intelligent LLM based Agent for Autonomous Clinical Trial Data Analysis |
Yu Peng,
Michael Wang |
source |
14 |
| PharmaSUG |
2024 |
A 'Shiny' New Perspective: Unveiling Next-Generation Patient Profiles for Medical and Safety Monitoring |
Helena Belloff,
William Lee,
Melanie Hullings |
source |
8 |
| PharmaSUG |
2024 |
A Programmer-s Insight into an Alternative to TQT Study Data Submission |
Hiba Najeeb,
Raghavender Ranga |
source |
7 |
| PharmaSUG |
2024 |
Agile Sponsor Oversight of Statistical Programming Activities |
Manuela Koska,
Veronika Csom |
source |
6 |
| PharmaSUG |
2024 |
Agile, Collaborative, Efficient (ACE): A New Perspective on Data Monitoring Committee Data Review Preparation |
Ke Xiao |
source |
6 |
| PharmaSUG |
2024 |
An introduction to Quarto: A Versatile Open-Source Tool for Data Reporting and Visualization |
Joshua J. Cook |
source |
18 |
| PharmaSUG |
2024 |
Around the Data DOSE-y Doe, How Much Fun Can Your Data Can Be: Using DOSExx Variables within ADaM Data Sets |
Inka Leprince,
Richann J. Watson |
source |
12 |
| PharmaSUG |
2024 |
Automation of Report Generation Beyond Macro |
Hong Qi,
Mary N. Varughese |
source |
6 |
| PharmaSUG |
2024 |
AutoVis Oncology Presenter: Automated Python-Driven Statistical Analysis and Visualizations for Powerful Presentations |
Indraneel Narisetty |
source |
12 |
| PharmaSUG |
2024 |
Benefits, Challenges, and Opportunities with Open-source Software (OSS) Integration |
Kirk Paul Lafler,
Ryan Paul Lafler,
Joshua J. Cook,
Stephen B. Sloan |
source |
7 |
| PharmaSUG |
2024 |
Bridging AI and Clinical Research: A New Era of Data Management with ChatGPT |
Illia Skliar |
source |
12 |
| PharmaSUG |
2024 |
Comprehensive Evaluation of Large Language Models (LLMs) Such as ChatGPT in Biostatistics and Statistical Programming |
Songgu Xie,
Michael Pannucci,
Weiming Du,
Huibo Xu,
Toshio Kimura |
source |
9 |
| PharmaSUG |
2024 |
Cultivating Success with Non-standard Investigator-sponsored Trial Data for FDA Submissions |
Jai Deep Mittapalli,
Jinit Mistry,
Venkatesulu Salla |
source |
9 |
| PharmaSUG |
2024 |
Data Harmony Revolution: Rocking Trials with Clinical Data Literacy |
Melanie Hullings,
Emily Murphy,
Andrew Burd,
Helena Belloff |
source |
5 |
| PharmaSUG |
2024 |
Data Literacy 101: Understanding Data and Extracting Insights |
Kirk Paul Lafler |
source |
9 |
| PharmaSUG |
2024 |
Efficient Repetitive Task Handling in SAS Programming Through Macro Loops |
Chary Akmyradov |
source |
7 |
| PharmaSUG |
2024 |
Embracing Diversity in Statistical Computing Environments: A Multi-Language Approach |
Amit Javkhedkar,
Sridhar Vijendra |
source |
6 |
| PharmaSUG |
2024 |
Enhancing FDA Debarment List Compliance through Automated Data Analysis Using Python and SAS |
Yongjiang (Jerry) Xu,
Karen Xu,
Suzanne Viselli |
source |
6 |
| PharmaSUG |
2024 |
Exploit the Window of Opportunity: Exploring the Use of Analysis Windowing Variables |
Richann J. Watson,
Elizabeth Dennis,
Karl Miller |
source |
4 |
| PharmaSUG |
2024 |
Facilitating Seamless SAS-to-R Transition in Clinical Data Analysis: A Finetuned LLM Approach |
Chaitanya Pradeep Repaka,
Santhosh Karra |
source |
6 |
| PharmaSUG |
2024 |
Game changer! The new CDISC ADaM domain ADNCA for PK/PD data analysis |
Santosh Ranjan |
source |
7 |
| PharmaSUG |
2024 |
GenAI to Enhance Your Statistical Programming |
Philip Bowsher |
source |
13 |
| PharmaSUG |
2024 |
iCSR: A Wormhole to Interactive Data Exploration Universe |
Sudhir Kedare,
Steve Wade,
Chen Yang,
Matthew Travell,
Jagan Mohan Achi |
source |
7 |
| PharmaSUG |
2024 |
Implementation of composite estimands for responder analysis based on change from baseline in non-solid tumours |
Reshma Radhakrishnan |
source |
11 |
| PharmaSUG |
2024 |
Interfacing with Large-scale Clinical Trials Data: The Database for Aggregate Analysis of ClinicalTrials.gov |
Joshua J. Cook,
Achraf Cohen |
source |
16 |
| PharmaSUG |
2024 |
MLNR or Machine Learning in R |
Chuck Kincaid |
source |
23 |
| PharmaSUG |
2024 |
Opportunities and Challenges for R as an open-sourced solution for statistical analysis and reporting, from vendor's perspective |
Peng Zhang,
Lizhong Liu,
Tai Xie |
source |
8 |
| PharmaSUG |
2024 |
Optimizing Clinical Data Processes: Harnessing the Power of Metadata Repository (MDR) for Innovative Study Design (ISD) and Integrated Summary of Safety (ISS) / Efficacy (ISE) |
Lakshmi Mantha,
Purvi Kalra,
Arunateja Gottapu |
source |
9 |
| PharmaSUG |
2024 |
Piloting into the Future: Publicly available R-based Submissions to the FDA |
Benjamin Straub |
source |
9 |
| PharmaSUG |
2024 |
Quality Assurance within Statistical Programming: A Systemic Way to Improve Quality Control |
Todd Case,
Margaret Huang |
source |
4 |
| PharmaSUG |
2024 |
Reimagining reporting and Visualization during clinical data management |
Vandita Tripathi,
Manas Saha |
source |
9 |
| PharmaSUG |
2024 |
Streamlining Patient-reported outcome (PRO) data standardization & analysis |
Varsha Mithun Patil,
Mrityunjay Kumar |
source |
9 |
| PharmaSUG |
2024 |
Ten Rules for Better Charts, Figures and Visuals |
Kirk Paul Lafler |
source |
19 |
| PharmaSUG |
2024 |
Translation from statistical to programming: effective communication between programmers and statisticians |
Diana Avetisian |
source |
10 |
| PharmaSUG |
2024 |
Unraveling the Layers within Neural Networks: Designing Artificial and Convolutional Neural Networks for Classification and Regression Using Python-s Keras & TensorFlow |
Ryan Paul Lafler,
Anna T. K. Wade |
source |
18 |
| PharmaSUG |
2024 |
Visual discovery in Risk-Based Monitoring using topological models |
Kostiantyn Drach,
Iryna Kotenko |
source |
31 |
| PHUSE US |
2024 |
Agile, Collaborative, Efficient (ACE): A New Perspective on Data Monitoring Committee Data Review Preparation |
Ke Xiao,
Hong Wang |
source
poster source |
6 |
| PHUSE US |
2024 |
AI-Facilitated Monitoring Methods and Techniques to Enhance Participant Safety and Data Integrity |
Kris Wenzel,
Martin Bauwens |
source
presentation source |
6 |
| PHUSE US |
2024 |
Analysis of Same Objective - Different SAS Procedures: How to Choose a SAS Procedure Wisely for a Statistical Analysis? |
Pradeep Acharya,
Ephicacy Lifescience |
source
presentation source |
9 |
| PHUSE US |
2024 |
Approaching End-to-End Analysis Standardisation in Global and Therapeutic Areas Level |
Rudra Sheth,
Xiaohan Zou |
source
presentation source |
4 |
| PHUSE US |
2024 |
Automating TLG Generation for Clinical Trials Leveraging R/R Shiny Technology and Cross-Therapeutic Area Expertise |
Vijay Sharma,
Margaret Wishart |
source
presentation source |
6 |
| PHUSE US |
2024 |
Automation of Exploratory Report Generation using R shiny and R Markdown |
Denny Sebastian |
source
poster source |
7 |
| PHUSE US |
2024 |
Beyond the Hype: A Pragmatic Approach to Leveraging AI/ML for Data Review |
Robert Musterer |
source
presentation source |
10 |
| PHUSE US |
2024 |
Build an Effective and High-Performance Team |
Helen Yang,
Richa Kala |
source
presentation source |
4 |
| PHUSE US |
2024 |
Change Management: A futuristic opportunity for SAS Programmers to build R Library |
Shashikant Kumar,
Ephicacy Lifescience |
source
presentation source |
6 |
| PHUSE US |
2024 |
Codeless Queries: Harnessing AI to Translate Clinical Trial Questions into Custom Listings Through Intuitive UI Interactions |
Aditya Gadiko |
source
presentation source |
7 |
| PHUSE US |
2024 |
Comprehensive Evaluation of Large Language Models (LLMs) Such as ChatGPT in Biostatistics and Statistical Programming |
Toshio Kimura,
Michael Pannucci |
source
presentation source |
9 |
| PHUSE US |
2024 |
Data Designer: Empowering data mapping, manipulation and analysis for advanced insights and decision making |
Mukul K Mittal |
source
presentation source |
6 |
| PHUSE US |
2024 |
Data Pipeline - Improving Cycle Time and Shifting Data Closer to Analytics |
Jayasree Ivaturi |
source
presentation source |
6 |
| PHUSE US |
2024 |
Demystifying Submissions to NMPA China [presentation] |
Hiral Raval,
Dyuthi Yellamraju |
source |
19 |
| PHUSE US |
2024 |
Developing Leadership, Fostering Collaboration and Building Perspective Through External Communities |
Harper Forbes |
source
presentation source |
2 |
| PHUSE US |
2024 |
Digitisation of Specifications - Brave New World for Analysis Definitions |
Rebecca Bates,
Krishna Gopal |
source
presentation source |
6 |
| PHUSE US |
2024 |
Effortless Table Generation: A SAS Macro for Streamlining Your Workflow |
Zhen (Laura) Li |
source
presentation source |
12 |
| PHUSE US |
2024 |
Empowering Excellence: Strategies for Cultivating a Culture of Bold Decision-Making in Teams |
Mark Bynens |
source |
8 |
| PHUSE US |
2024 |
Enabling the Breakthroughs of Tomorrow: The Data Lakehouse for Clinical Trials |
Venu Mallarapu |
source
presentation source |
12 |
| PHUSE US |
2024 |
Enabling the Interoperable Data Ecosystem with the elluminate Clinical Data Cloud [presentation] |
Nathan Johnson |
source |
15 |
| PHUSE US |
2024 |
Expanding Collaboration and Innovation in R&D: Leveraging the Power of Open-Source Tools |
Ellis Hughes |
source
presentation source |
3 |
| PHUSE US |
2024 |
From Missing to Meaningful: Tackling Partial Dates in Clinical Trials |
Bhargav Koduru |
source
poster source |
4 |
| PHUSE US |
2024 |
Future-Proofing Clinical Data Sciences: The Pivotal Role of Therapeutic Area Proficiency |
Sascha Ahrweiler |
source
presentation source |
12 |
| PHUSE US |
2024 |
How No-Code Visualisation is Fast Becoming an Asset for Data Engineering and Data Science Teams |
Pritesh Desai |
source
presentation source |
6 |
| PHUSE US |
2024 |
iCSR: A Wormhole to the Interactive Data Exploration Universe |
Sudhir Kedare,
Steve Wade |
source
presentation source |
7 |
| PHUSE US |
2024 |
Leadership Insights - Let's Learn How to Lead the Leaders |
Rachna Mittal |
source
presentation source |
4 |
| PHUSE US |
2024 |
Leading Teams Through Clinical Data Transformation with Storytelling |
Alison Banda,
Katrina Rice |
source
presentation source |
3 |
| PHUSE US |
2024 |
Real-World Application of Natural Language Processing: More Than Just Sentiment Analyses |
Scott McClain |
source
presentation source |
7 |
| PHUSE US |
2024 |
Revolutionize Clinical Trial Data Exploration with teal |
Chendi Liao,
Dony Unardi |
source
presentation source |
6 |
| PHUSE US |
2024 |
Risk-Based Monitoring Using AI/ML Detection of Systematic Bias in Clinical Data |
Kostiantyn Drach,
Sergey Glushakov |
source
presentation source |
12 |
| PHUSE US |
2024 |
SAS PROC MI: Your Impeccable Tool for Enhanced Data Analysis Through the Lens of Multiple Imputation |
Anush Kurghinyan,
Shahrzad Talebian |
source
presentation source |
7 |
| PHUSE US |
2024 |
SPACE - GSK Biostatistics continues its journey to a new frontier |
Eileen Ching |
source
presentation source |
9 |
| PHUSE US |
2024 |
Statistical Monitoring Report: A Path Forward to Interactive Data Analysis and Quantitative Decision-Making |
Debopriya Ghosh |
source
presentation source |
3 |
| PHUSE US |
2024 |
Teal.builder: A Multifaceted Teal App Builder for Clinical Data Exploration and Reporting |
Freeman Wang,
Andre Couturier |
source
presentation source |
5 |
| PHUSE US |
2024 |
Validation Unveiled: Striking the Balance for Data Integrity and Compliance in R, Python, and SAS |
Sy J. Truong |
source
presentation source |
10 |
| PHUSE US |
2024 |
What Role Does ChatGPT Have in your Clinical Programming? |
Andy Ratcliffe |
source
presentation source |
7 |
| PHUSE US |
2024 |
Whodunnit? Automation Tools Accelerate Statistical Analysis in an SCE with Full Compliance [presentation] |
Shivoy Pandita,
Jörn Bilow |
source |
13 |
| PHUSE EU |
2023 |
Automation and Orchestration of Data Science Applications Using OpenAPI |
Dmitry Zakharov,
Alexander Lüders |
source
presentation source |
3 |
| PHUSE EU |
2023 |
Avoid Major Pitfalls When Using Real-World Evidence (RWE) in Regulatory Submissions |
Alex Ide,
Mark Lambrecht |
source
presentation source |
3 |
| PHUSE EU |
2023 |
Boosting SAS Programming Efficiency with ChatGPT: A Clinical Trials Perspective |
Illia Skliar |
source
presentation source |
11 |
| PHUSE EU |
2023 |
Challenges in Oncology Modular studies: The Fortrea approach |
Francesca Dall'Acqua |
source
presentation source |
7 |
| PHUSE EU |
2023 |
Comparing Analysis Method Implementations in Software (CAMIS): An Open Source Repository to Document Differences in Statistical Methodology Across Software |
Christina Fillmore |
source
presentation source |
7 |
| PHUSE EU |
2023 |
Data Managers and R Programming: The Unlikely Pair |
Anaelle Perretti (Bonetta) |
source
presentation source |
9 |
| PHUSE EU |
2023 |
Dataset-JSON [presentation] |
Samuel Hume,
Jesse Anderson |
source |
26 |
| PHUSE EU |
2023 |
Design Considerations for Building a System for Automated Statistical Analysis |
Nicolai Skov Johnsen,
Christian Olsen |
source
presentation source |
6 |
| PHUSE EU |
2023 |
Developing a Shiny Web Application to Address Suboptimal Treatment of Urology Patients Through Predictive Modelling and Improved Communication of Science |
Federico Concas,
Juan Manuel Palacios-Moreno |
source
presentation source |
5 |
| PHUSE EU |
2023 |
Drafting Your Plain Language Summaries: Hurdles to Overcome and How to Overcome Them |
Eliza Gray |
source
presentation source |
8 |
| PHUSE EU |
2023 |
Efficacy Analyses with Imputations: Methods, Limitations and Lessons Learned |
Amine Khemiri |
source
presentation source |
3 |
| PHUSE EU |
2023 |
Experiences of Training Teams in R |
Alanah Jonas |
source
presentation source |
10 |
| PHUSE EU |
2023 |
Generative AI: A Case Study Highlighting the Potential and the Risks |
Nikolay Manchev,
Michael Harnish |
source
presentation source |
23 |
| PHUSE EU |
2023 |
Getting ready for R |
Kieran Martin,
Welwyn Garden |
source
presentation source |
6 |
| PHUSE EU |
2023 |
GPT (Generative Pretrained Transformers) and LLM (Large Language Models) have generated a lot of attention since their inception in early 2023 with the advent of OpenAI GPT3.5, then GPT4.0 |
Jerome Vetillard,
Mark Lambrecht |
source
presentation source |
16 |
| PHUSE EU |
2023 |
How Can Python Be Used in Clinical Trials? |
Andrés Käsa,
Matt Davies,
Pierre Dostie |
source
presentation source |
21 |
| PHUSE EU |
2023 |
How to Get Started in Pharma and How We Can Help Those Starting Out [poster] |
Saskia Leserer,
Lara Suckut |
source |
1 |
| PHUSE EU |
2023 |
Increasing Trend of Biomarker Analysis in Clinical Trials |
Anjali Ranga |
source
presentation source |
11 |
| PHUSE EU |
2023 |
Interaction with the FDA During and After a Type C Meeting, From the Perspective of a Statistical Programmer |
Dieter Hartz |
source
presentation source |
5 |
| PHUSE EU |
2023 |
It's Easy Peasy Submitting Data to the China NMPA - Really? |
Nigel Montgomery,
Chenkai Lv |
source
presentation source |
10 |
| PHUSE EU |
2023 |
Management impact on Employee Engagement - Statistical Programmers in Focus |
Wickus Bronkhorst |
source
presentation source |
7 |
| PHUSE EU |
2023 |
Mr. ight - Why R Should Be Used for Validating TLFs in Clinical Trials? |
Monika Ludwinska |
source
presentation source |
10 |
| PHUSE EU |
2023 |
Patient Profiles v2.0: Easy and Quick Clinical Trial Insights in Tableau |
Roman Radelicki,
Annelies Van Zeveren |
source
presentation source |
6 |
| PHUSE EU |
2023 |
Practical Operations of Electronic Study Data Submissions |
Priyanka Pujari |
source
presentation source |
9 |
| PHUSE EU |
2023 |
Revolutionising Data Exploration: An Interactive Journey Through R Shiny [presentation] |
Valentin Legras |
source |
30 |
| PHUSE EU |
2023 |
Road to Rome or Roaming - A Reprise [presentation] |
Francis Kendall,
Christian Mueller |
source |
32 |
| PHUSE EU |
2023 |
Statistical Programming 101 for the Fourth Industrial Revolution |
Ritika Aggarwal |
source
presentation source |
10 |
| PHUSE EU |
2023 |
Stay Ahead of the Curve: Learn About Leapfrogging as a Statistical Programmer |
Jitendra Singh,
Kavita Dargan |
source
presentation source |
4 |
| PHUSE EU |
2023 |
Streamlining Clinical Data Analysis and Reporting with R: Best Practices, Tips and Techniques for Efficient Workflow Management and Code Optimisation |
Vaibhavi Govind Bhide,
Perry Meeks |
source
presentation source |
12 |
| PHUSE EU |
2023 |
Submission Standards for Real-World Data: Gaps, Limitations and Recommendations |
Jeffrey M. Abolafia,
Sarah Ferko,
Ingeborg Holt |
source
presentation source |
8 |
| PHUSE EU |
2023 |
The Curious Case of Observational Studies - A Programmer's Dilemma |
Vikas Shokeen |
source
presentation source |
11 |
| PHUSE EU |
2023 |
The Digital Protocol Is Just the Beginning. Or Is It? [presentation] |
Thierry Philippe,
Bill Qubeck |
source |
17 |
| PHUSE EU |
2023 |
The Evolving Role of Statistical Programmers in the Pharmaceutical Industry: The Impact of Artificial Intelligence |
Cindy Marabotti |
source
poster source |
8 |
| PHUSE EU |
2023 |
Unleashing the Power of Large Language Models for Clinical Data Approaches: Will AI chatbots like ChatGPT/Bard replace statistical programmer and statisticians over time? |
Ercan Suekuer |
source
presentation source |
9 |
| PHUSE EU |
2023 |
Unleashing the Role of a Statistical Programmer in Expediting a Submission, Novartis |
Sowmya Singuluri |
source
presentation source |
7 |
| PHUSE EU |
2023 |
Will R/Shiny Provide a Novel Way for Study Teams to Review Clinical Data? |
Gustav Söderström |
source
presentation source |
3 |
| WUSS |
2023 |
From Interactive Mapmaking to Beautiful Geospatial Visualizations: Harnessing the Power of Python and Google Earth Engine for Extracting, Analyzing, and Visualizing High Resolution Spatiotemporal Data |
Ryan Paul Lafler,
Anna T. K. Wade |
source |
23 |
| WUSS |
2023 |
How to Assemble Macros from Metadata and Execute them |
Karen Walker |
source |
12 |
| WUSS |
2023 |
Navigating SAS and CDISC Certification with Apprenticeship |
Sarvar Khamidov |
source |
7 |
| WUSS |
2023 |
Ten Rules for Better Charts, Figures and Visuals |
Kirk Paul Lafler |
source |
19 |
| WUSS |
2023 |
Univariate Outlier Detection Using SAS |
Fan Yang |
source |
12 |
| WUSS |
2023 |
Unraveling the Layers within Neural Networks: Designing Artificial and Convolutional Neural Networks for Classification and Regression Tasks using TensorFlow in Python |
Ryan Paul Lafler,
Anna T. K. Wade |
source |
24 |
| WUSS |
2023 |
What's next after model comparison? Model selection and model averaging in SAS |
Chong Ho Yu,
Charlene Yang |
source |
14 |
| SESUG |
2023 |
%modelselect: A macro for automatically selecting statistical models based on fit statistics |
William B. Smith |
source |
7 |
| SESUG |
2023 |
CAMIS: Comparing Analysis Method Implementations in Software |
Brian K. Varney |
source |
4 |
| SESUG |
2023 |
Exploring the Skills Needed by the Data Scientist / Analytics Professional |
Kirk Paul Lafler |
source |
14 |
| SESUG |
2023 |
For Clinical Trials: A Faster and Smoother Approach to Create your SDTM and ADAM Define Specifications for Define.xml with SAS |
Star Nze |
source |
29 |
| SESUG |
2023 |
Generate and Customize eDISH Plot to Identify Hy's Law Cases in Simple Steps |
Jeetender Chauhan,
Sarad Nepal,
Madhusudhan Ginnaram |
source |
10 |
| SESUG |
2023 |
Longitudinal Analysis of Marital Therapy's Impact on Intimacy in Heterosexual Couples |
Yaa Awuah,
Mostafa Zahed |
source |
19 |
| SESUG |
2023 |
Predicting Employees' Preference for Remote or On-site Jobs |
Livingstone Gadzanku |
source |
10 |
| SESUG |
2023 |
Translating Common Data Visualizations from PROC SGPLOT to ggplot2 |
Austin R. Brown |
source |
11 |
| PharmaSUG |
2023 |
Acceleration and automation of genomic data analysis to meet corporate compliance standards using advanced cloud components |
Gopal Joshi,
Satyoki Chatterjee,
Pankaj Choudhary,
Sanjay Koshatwar,
Shekhar Seera |
source |
11 |
| PharmaSUG |
2023 |
An End-to-End and Fully Integrated Clinical Development Platform with eDC/Labs data Data Management, Medical Review, Statistical Analysis and Adaptive Design etc. |
Peter Wang,
Vindyala Sunil |
source |
6 |
| PharmaSUG |
2023 |
Bringing it All Together: Applying the Analytics Life Cycle for Natural Language Processing to Life Sciences |
Sundaresh Sankaran,
Tom Sabo |
source |
15 |
| PharmaSUG |
2023 |
Building an Internal R Package for Statistical Analysis and Reporting in Clinical Trials: A SAS User-s Perspective |
Huei-Ling Chen,
Heng Zhou,
Nan Xiao |
source |
11 |
| PharmaSUG |
2023 |
CDISC Conformance and Compliance: So Many Resources, So Little Time! |
Jennifer K. Fulton,
Stephen Black |
source |
11 |
| PharmaSUG |
2023 |
From Sea to shining sea - End to End discussion on PR and LB data |
Abraham Yeh |
source |
7 |
| PharmaSUG |
2023 |
Guidelines for the Statistical Analysis in German Dossier Submissions |
Meiling Gao,
Xi Qian,
Hui Mao |
source |
8 |
| PharmaSUG |
2023 |
Integrating Practices: How Statistical Programmers Differ and Align Within User Groups |
Valeria Duran,
Radhika Etikala,
Haimavati Rammohan |
source |
15 |
| PharmaSUG |
2023 |
Key Statistical Programming Considerations in External Collaborative Clinical Trials |
James Zhao,
Hong Qi,
Mary N. Varughese |
source |
4 |
| PharmaSUG |
2023 |
Leverage and Enhance CDISC TAUGs to Build More Traceability for and Streamline Development of Efficacy ADaM in Oncology Studies |
Xiangchen (Bob) Cui |
source |
29 |
| PharmaSUG |
2023 |
Macro to Automate Creation and Sync of Shell Document and TOC |
Karen Walker,
Jeff Cao |
source |
10 |
| PharmaSUG |
2023 |
Macro To Automate Crossover Review In Produced Outputs |
Igor Goldfarb,
Ella Zelichonok |
source |
25 |
| PharmaSUG |
2023 |
Masters of the Table Universe: Creating Table Shells Consistently and Efficiently Across All Studies |
Michael Hagendoorn,
Ran Li,
Mimi Vigil,
Shan Yang |
source |
15 |
| PharmaSUG |
2023 |
Meta-Analysis in R |
Lin Gu |
source |
8 |
| PharmaSUG |
2023 |
SAS-based Method for PK Noncompartmental Analysis and Validation |
Hui Mao,
Lixin Gao |
source |
5 |
| PharmaSUG |
2023 |
SDTM Variables You Might Forget About |
Nadiia Pukhliar,
Dariia Tsyhanenko,
Iryna Kotenko |
source |
10 |
| PharmaSUG |
2023 |
Sensitivity Analysis for Missing Data Using Control-based Pattern Imputation |
Jun Feng,
Jingmin Liu |
source |
7 |
| PharmaSUG |
2023 |
Shifting the drug development paradigm with Adaptive Design and master protocol |
Aman Bahl |
source |
16 |
| PharmaSUG |
2023 |
Statistical Considerations and Methods for Handling Missing Outcome Data in Clinical Trials During the Era of COVID-19 |
Xi Qian,
Chengfei Lu |
source |
11 |
| PharmaSUG |
2023 |
Ten Rules for Better Charts, Figures and Visuals |
Kirk Paul Lafler |
source |
19 |
| PharmaSUG |
2023 |
Using R to Create Population Pharmacokinetic Dataset |
Yangwei Yan,
Prema Sukumar,
Neelima Thanneer |
source |
10 |
| PharmaSUG |
2023 |
Validating novel maraca plots - R and SAS love story |
Nicole Major,
Srivathsa Ravikiran,
Monika Huhn,
Samvel Gasparyan,
Martin Karpefors |
source |
17 |
| PharmaSUG |
2023 |
Why FDA Medical Queries (FMQs) for Adverse Events of Special Interest? Implementation and Case Study |
Clio Wu |
source |
12 |
| PHUSE US |
2023 |
A Pragmatic Approach to Data Cleaning - Decisions in Selecting When to Apply AI/ML [presentation] |
Robert Musterer,
Alison Banda |
source |
15 |
| PHUSE US |
2023 |
A Standard Data Set Format for the Validation of Tables and Listings in Regulatory Submissions for Clinical Trials |
Kevin R. Viel |
source
poster source |
10 |
| PHUSE US |
2023 |
A TransCelerate Initiative: Paving the Way for the Adoption of Modernized Statistical Analytics [presentation] |
Nicholas Masel |
source |
12 |
| PHUSE US |
2023 |
AccelerateR - Utilising Supporting and Mentoring for Delivering a Statistical Package in R [presentation] |
Benjamin Arancibia |
source
video |
17 |
| PHUSE US |
2023 |
An introduction to NEST, an open-sourced R toolkit for TFL delivery and interactive data displays used in all new Roche trials [presentation] |
Vincent Shen,
James Black |
source
video |
35 |
| PHUSE US |
2023 |
An Open-Sourced R Package for Streamlining Generation of Standard TLFs in Both Static and Interactive Formats [presentation] |
Lena Wang,
Heng Wang |
source
video |
25 |
| PHUSE US |
2023 |
Approachable and Scalable Web Application Solutions Using Shiny for Python and R Shiny in the Pharmaceutical Industry |
Vikash Jain,
Denny Sebastian |
source
presentation source |
9 |
| PHUSE US |
2023 |
Automation of ADaM Dataset & TFL Visualization Through an R Package - GenAdam2 |
Mahesh Divakaran |
source
presentation source |
5 |
| PHUSE US |
2023 |
Balance Between Humans and Machines - How NLP Helps Translate Text Specification to Code, and Vice Versa |
Hao (Harry) Chen,
Jaimin Patel |
source
presentation source |
9 |
| PHUSE US |
2023 |
Big Pharma Acquires Biotech - Perceptions from The Clinical Data Scientists' Point of View |
Jonas Poulsson,
Henning Pontoppidan Föh |
source
presentation source |
10 |
| PHUSE US |
2023 |
Build vs Buy for SCE: Considerations for the Future of the Statistical Computing Environment (SCE) [presentation] |
Nathan Johnson,
Alison Banda |
source
video |
20 |
| PHUSE US |
2023 |
Connecting Tables, Listings and Figures [presentation] |
Stella Guo |
source
video |
11 |
| PHUSE US |
2023 |
Digging Deep into Digital Biomarkers: Empowering Clinical Trials |
Vijay Pasapula,
Gianna Huang |
source
presentation source |
12 |
| PHUSE US |
2023 |
Enabling Comprehensive Interactive Data Analysis and Exploration in R with an Open-Sourced, Scalable Shiny Framework [presentation] |
Dony Unardi,
Chendi Liao |
source
video |
17 |
| PHUSE US |
2023 |
Future Workforce: How to invest in your team through Innovative transformation |
Limna Salim |
source
presentation source |
8 |
| PHUSE US |
2023 |
Handling Multiple Adaptations in One Clinical Trial |
Parvee Kumar,
Shrutimita Pokhariyal |
source
presentation source |
6 |
| PHUSE US |
2023 |
If Data is the New Oil, How Do You Make the Most of Your Reserves? |
Simon Luo,
Ashley Mao |
source
presentation source |
4 |
| PHUSE US |
2023 |
Innovate Clinical Trial Reporting with Open Source |
Soma Sekhar Sriadibhatla,
Francis Kendall |
source
presentation source |
4 |
| PHUSE US |
2023 |
Investigator Initiated Trials: Turbulence ahead! |
Helen Liu,
Vineet Mathur |
source
presentation source |
3 |
| PHUSE US |
2023 |
Journey of SCE Implementation [poster] |
Timothy D. Kelly,
Kala Shivali |
source |
1 |
| PHUSE US |
2023 |
Master Protocol Design: Advantages and Challenges in Vaccine Clinical Trials [presentation] |
Janaki Shankaran,
Meenal Gawas |
source
video |
19 |
| PHUSE US |
2023 |
New Application Adaptation with Business Continuity [presentation] |
Subhayan Das,
Kala Shivali |
source
video |
12 |
| PHUSE US |
2023 |
Parametric Event-prediction for Time-to-event Data in Clinical Trials [presentation] |
Jingyuan Chen,
Weijie Zhang |
source
video |
22 |
| PHUSE US |
2023 |
Performing Propensity-score-integrated Comparative Analysis in External Control Arm Studies Using R [presentation] |
Lixiao Chen,
Lorraine Fang |
source
video |
20 |
| PHUSE US |
2023 |
Recasting Trial Designs with Digital Endpoints: A SWOT Analysis |
Kishore Shyamala |
source
presentation source |
7 |
| PHUSE US |
2023 |
Retain and Grow the Talent in Statistical Programming |
Madhusudhan Reddy Papasani |
source
presentation source |
6 |
| PHUSE US |
2023 |
SIGMA: What is the Sum of its Impact on Pfizer's Statistical A&R Space? [presentation] |
Christopher J. Colangelo |
source
video |
12 |
| PHUSE US |
2023 |
Snow White & the 7 Keys for Data Lake Hydration [presentation] |
Chris Decker,
Kate McMahon |
source
video |
23 |
| PHUSE US |
2023 |
Staying Alert to Data Quality: A Shiny App to Visualise the Electronic Patient Reported Outcome (ePRO) Data |
Wenyi Liu |
source
presentation source |
6 |
| PHUSE US |
2023 |
The Role of Open Source for Data Science, Engineering and Programming Teams in the Pharma Industry [presentation] |
Tadeusz Lewandowski,
Axel Muehlig |
source
video |
17 |
| PHUSE US |
2023 |
Up-to-Date with Dates - Imputation Rules in R Compared to SAS |
Monika Ludwinska |
source
presentation source |
10 |
| PHUSE US |
2023 |
Using R for Automatically Managing Clinical Trial Data Issues [presentation] |
Jessica Riedy,
Jessica Higgins |
source
video |
9 |
| PHUSE US |
2023 |
Visual Guidance: Monitoring Data Fitness and Study Progress in an SCE [presentation] |
Jörn Bilow |
source
video |
12 |
| PHUSE US |
2023 |
What is the Business Value of Your Own Automated Computing Workspace? [presentation] |
Roger Chivers,
Chris Decker |
source |
13 |
| PHUSE US |
2023 |
Why Roche is Investing into Building Open-Source Software for Clinical Reporting [presentation] |
Thomas Neitmann |
source
video |
16 |
| PHUSE EU |
2022 |
AI_PREMie: Saving Lives of Mothers and Babies Using AI [presentation] |
Patricia Maguire,
John Curran |
source |
26 |
| PHUSE EU |
2022 |
An Automated Approach to Generating Call Programs from an Analysis Request |
David Maher-McWilliams,
Michael Allie |
source
presentation source |
9 |
| PHUSE EU |
2022 |
Automation in Biostatistics at Novo Nordisk [presentation] |
Matthew Phelps |
source
video |
37 |
| PHUSE EU |
2022 |
Automation of Standard ADaM Variables Through an R Package - GenAdam |
Mahesh Divakaran |
source
presentation source |
8 |
| PHUSE EU |
2022 |
Breaking Down the Data Standards Silos - A New Metadata Ontology for Data Analysis Derivations |
Chris Price,
Nelia Lasierra |
source
presentation source |
7 |
| PHUSE EU |
2022 |
CDISC Analysis Results Standard - Update and Progress |
Karl Wallendszus,
Hansjörg Frenzel |
source
presentation source |
7 |
| PHUSE EU |
2022 |
Collaboration Between Analytical Health Care Technology Leaders will Positively Impact Clinical Trial Research Innovation & Improve Health Care System [presentation] |
Mark Lambrecht,
Andrew Warrington |
source
video |
19 |
| PHUSE EU |
2022 |
Data Catalogues - The new Showman to organize your data, A CRO perspective |
Limna Salim |
source
presentation source |
8 |
| PHUSE EU |
2022 |
Deep Learning to Classify Adverse Events from Patient Narratives [presentation] |
Qais Hatim,
Tom Sabo |
source
video |
12 |
| PHUSE EU |
2022 |
Effective NLP API Access to Unstructured Text for Downstream Analysis and Models in Pharma: Bench to Bedside [presentation] |
Jane Reed |
source
video |
26 |
| PHUSE EU |
2022 |
Evolving into Data Science. What Has Changed? [presentation] |
Sarah Kirk,
Ivan Robinson |
source
video |
19 |
| PHUSE EU |
2022 |
Exploratory Analysis - People-powered Pathways to Success within a Critical Risk-based Approach [presentation] |
Simon Jackson |
source
video |
21 |
| PHUSE EU |
2022 |
From Artifact to Metadata: A Divergent Approach to Automation Through Standardisation |
Nicolas Rouillé,
Camie Britton |
source
presentation source |
4 |
| PHUSE EU |
2022 |
From Stored Process to Job Execution - Build Your SAS (Lego) App [presentation] |
Olivier Bouchard |
source
video |
14 |
| PHUSE EU |
2022 |
Governance and Cataloguing of Analytics Assets [presentation] |
Paul McCaffery,
Clement Benemara |
source |
15 |
| PHUSE EU |
2022 |
My Journey from SAS to R [presentation] |
Lucy Watson |
source |
15 |
| PHUSE EU |
2022 |
Overcoming Challenges of Your Integrated Summary ISS/ISE Submissions |
Jenet Cp,
Akhil Vijayan |
source
presentation source |
7 |
| PHUSE EU |
2022 |
Performance Traps in Multiple Imputation Analysis Using Mixed Model Repeated Measures [presentation] |
Piotr Karasiewicz |
source
video |
17 |
| PHUSE EU |
2022 |
Python to Automate an AR Project Identifying Discrepancies across Fields from a Government Open-source Dataset of COVID-19 Vaccine Registrations |
Aldir Medeiros Filho |
source
video
presentation source |
14 |
| PHUSE EU |
2022 |
R Shiny Apps: To QC or Not to QC? [presentation] |
Katie Withycombe |
source
video |
19 |
| PHUSE EU |
2022 |
SAS and Python Working Together [presentation] |
Jim Box |
source |
18 |
| PHUSE EU |
2022 |
Statistical Methods for Finding Human Bias in Machine Learning Models [presentation] |
Jim Box |
source |
19 |
| PHUSE EU |
2022 |
The Integration Dilemma |
Angelo Tinazzi |
source
video
presentation source |
15 |
| PHUSE EU |
2022 |
The Role of Data Analytics Functions in Studies Utilising RWD for Submissions [presentation] |
Mark Graham,
Ravi Bahia |
source
video |
15 |
| PHUSE EU |
2022 |
Title:Pixel Plots: Identify Missing Data, See High-level Patterns and Break Axis Constraints |
Paul Grimsey |
source
presentation source |
16 |
| PHUSE EU |
2022 |
Trimmed Mean Analysis Is Not Rocket Science [presentation] |
Kateryna Fedoryshyna |
source
video |
18 |
| SESUG |
2022 |
Data for Good: Statistical Volunteering with SAS and How to Get Involved |
David J. Corliss |
source |
8 |
| SESUG |
2022 |
Don't be so One-Dimensional: How to Engineer Multi-Dimensional, High Cardinality Categorical Inputs for Machine Learning |
Aleksandar Nikolic |
source |
25 |
| SESUG |
2022 |
Exploring the Skills Needed by the Data Scientist |
Kirk Paul Lafler |
source |
13 |
| SESUG |
2022 |
SAS, SAS Coders, and IDEA (Inclusion, Diversity, Equity, Accessibility) |
Kelly D. Smith |
source |
6 |
| SESUG |
2022 |
Standardized, Customized or Both? Defining and Implementing (MedDRA) Queries in ADaM Data Sets |
Richann J. Watson,
Karl Miller |
source |
7 |
| SESUG |
2022 |
Statistical Analysis of School Shootings in the United States as Stochastic Terrorism |
David J. Corliss |
source |
8 |
| SESUG |
2022 |
Working with large decimals: how precise is my data with SAS? |
Osmel Brito Bigott,
Yenireth Gil,
María Victoria Daboín |
source |
4 |
| SAS Explore |
2022 |
SAS Viya with SingleStore: Maximize the Value of Your Data [video] |
Bill Danker,
Jason Secosky |
source
youtube |
|
| SAS Explore |
2022 |
SAS Viya With SingleStore: Maximize the Value of Your Data [DEMO] [video] |
Bill Danker |
source |
|
| SAS Explore |
2022 |
Struggling with Syntax? SAS Studio to the Rescue! [video] |
Jacqueline Johnson |
source
youtube |
|
| SAS Explore |
2022 |
The Batting Lab: Driving Home the Power of Data [video] |
Gunce Walton |
source |
|
| SAS Explore |
2022 |
The Chart Chasers! Finding Lost Revenue for Healthcare Providers [video] |
Shane Hanley |
source |
|
| SAS Explore |
2022 |
The Science Behind the Batting Lab [video] |
Gunce Walton |
source
youtube |
|
| SAS Explore |
2022 |
Unified ModelOps and Containerized Deployment for All Models [video] |
Glenn Clingroth,
Sophia Rowland |
source |
|
| WUSS |
2022 |
Complex heatmaps in Statistical analysis of Biomarkers and cancer genomics |
Yoganand Budumuru |
source |
18 |
| WUSS |
2022 |
Exploring the Skills Needed by the Data Scientist |
Kirk Paul Lafler |
source |
13 |
| WUSS |
2022 |
Heatmaps for Hot Housing Markets SAS an ultimate tool for analyzing real estate data [presentation] |
Harshita Budumuru |
source |
5 |
| WUSS |
2022 |
Quick Jumpstart into Pharmaceutical SAS Programming |
Jim Box,
Matthew J. Becker |
source |
7 |
| WUSS |
2022 |
Standardized, Customized or Both? Defining and Implementing (MedDRA) Queries in ADaM Data Sets |
Richann J. Watson,
Karl Miller |
source |
7 |
| WUSS |
2022 |
Ten Rules for Better Charts, Figures and Visuals |
Kirk Paul Lafler |
source |
19 |
| PharmaSUG |
2022 |
A Programmer's Perspective on Patient reported Outcomes in Oncology Trials |
Divya Vemulapalli |
source |
7 |
| PharmaSUG |
2022 |
Data Mining of Tables: The Barrier for Automation |
Ilan Carmeli |
source |
6 |
| PharmaSUG |
2022 |
Derivation of Efficacy Endpoints by iRECIST Criteria: A Practical Approach |
Ilya Krivelevich,
Lei Gao,
Richard Kennan |
source |
9 |
| PharmaSUG |
2022 |
Ensuring Distributed Data Custody on Cloud Platforms |
Ben E. Bocchicchio,
Sandeep Juneja |
source |
26 |
| PharmaSUG |
2022 |
Exploring R as a validation tool for statistical programming in clinical trials |
Uday Preetham Palukuru,
Runcheng Li,
Nilesh Patel,
Changhong Shi |
source |
11 |
| PharmaSUG |
2022 |
Implementing and Achieving Organizational R Training Objectives |
Jeff Cheng,
Abhilash Chimbirithy,
Amy Gillespie,
Yilong Zhang |
source |
8 |
| PharmaSUG |
2022 |
Making an ADaM Dataset Analysis-Ready |
Sandra Minjoe |
source |
10 |
| PharmaSUG |
2022 |
Quality Gates: An Overview from Clinical SAS Programming Perspective |
Nagadip Rao,
Pavan Jupelli |
source |
10 |
| PharmaSUG |
2022 |
R syntax for SAS programmers |
Max Cherny |
source |
12 |
| PharmaSUG |
2022 |
Rethinking Programming Assignments |
Scott Burroughs |
source |
4 |
| PharmaSUG |
2022 |
Unravel the mystery around NONMEM data sets for statistical programmers |
Sabarinath Sundaram,
Lyma Faroz |
source |
9 |
| PharmaSUG |
2022 |
Using R-Shiny Capabilities in Clinical Programming to create Applications |
Prakasam R,
Sujatha Kandukuri,
Tyagrajan Swaminathan |
source |
12 |
| PharmaSUG |
2022 |
Win Ratio Simulation For Power Calculation Made Easy |
Lili Li,
Roger Chang,
Benjamin Fine,
Yu-Chen Su |
source |
13 |
| PHUSE US |
2022 |
A Day on the Fast Track: How a Statistical Computing Environment Helps to Streamline Programming [presentation] |
Jörn Bilow |
source
video |
14 |
| PHUSE US |
2022 |
Applications of the R Package Validation Framework and {valtools} [presentation] |
Ellis Hughes |
source
video |
34 |
| PHUSE US |
2022 |
Bias in Machine Learning: Your Responsibilities as a Programmer [presentation] |
Jim Box |
source |
34 |
| PHUSE US |
2022 |
CDISC Analysis Results Standards - Approach and Development Update [presentation] |
Bess LeRoy,
Jeffrey M. Abolafia,
Bhavin Busa |
source |
18 |
| PHUSE US |
2022 |
Data Standardization at Scale with the elluminate Clinical Data Cloud [presentation] |
Nathan Johnson |
source |
19 |
| PHUSE US |
2022 |
Expand Your Insights by Utilizing Open-source Data Visualizations within Power BI [poster] |
Christopher C. Hurley |
source |
1 |
| PHUSE US |
2022 |
Integration of SAS LSAF and Veeva Using REST APIs [presentation] |
Ben E. Bocchicchio,
Pritesh Desai |
source |
16 |
| PHUSE US |
2022 |
Interactive Leadership Discussion Forum [presentation] |
Alison Batty,
Brian Hermann |
source |
13 |
| PHUSE US |
2022 |
Introducing Reporting Packages in R for TFLs [presentation] |
Pavan Reddy,
Thomas Kalfas |
source
video |
12 |
| PHUSE US |
2022 |
Patient Registries - Challenges and Opportunities [presentation] |
Sophia Zilber |
source |
20 |
| PHUSE US |
2022 |
R and its Application in Clinical Trial Data Analysis [presentation] |
Santosh Kumar Davuluri |
source
video |
21 |
| PHUSE US |
2022 |
SPACE - Launching GSK Biostatistics towards new horizons |
Eileen Ching |
source
presentation source |
10 |
| PHUSE US |
2022 |
Table Mining: The Barrier for Automation [presentation] |
Ilan Carmeli,
Mor Ram-On |
source |
16 |
| PHUSE US |
2022 |
The Complexity and Magnitude of Participant Reactogenicity Data [presentation] |
Gunasekaran Subramaniam,
Katrien Van der Donck |
source
video |
21 |
| PHUSE US |
2022 |
The Conversion of an SAS Macro to R [presentation] |
Franklin E. Menius |
source
video |
9 |
| PHUSE US |
2022 |
Transformation from Prescriptive Clinical Data Analyses to Dynamic Data-driven Analytics through the Adoption of Modularized Cloud Components [presentation] |
Andy Ratcliffe,
Chris Decker |
source |
35 |
| PHUSE US |
2022 |
We R in SPACE (Statistical Programming And Computing Environment). And We R Not Alone! [presentation] |
Alastair Scarlett,
Sumesh Kalappurakal |
source |
7 |
| PHUSE EU |
2021 |
A Beginner's Guide to Data Analysis |
Shuva Dey |
source
video |
15 |
| PHUSE EU |
2021 |
AI-powered Drug Development: Accelerating Trials with AI & ML [presentation] |
Raj Indupuri |
source
video |
10 |
| PHUSE EU |
2021 |
An Ongoing Modernisation Journey at Orion Pharma [presentation] |
Mark Lambrecht,
Olavi Kilkku |
source
video |
15 |
| PHUSE EU |
2021 |
Augmenting Therapeutic Effectiveness through Novel Analytics (ATHENA) - A Public-Private Partnership Project Funded by the Flemish Government (VLAIO) [presentation] |
Ploingarm Petsophonsakul,
Wouter Botermans |
source
video |
14 |
| PHUSE EU |
2021 |
Best Practices: Analysing Classical Clinical Trial Data with ML Methods [presentation] |
Uwe Pritzsche |
source
video |
10 |
| PHUSE EU |
2021 |
Building an SCE that Users Want to Use [presentation] |
Alastair Scarlett,
Chris Decker |
source
video |
9 |
| PHUSE EU |
2021 |
Creative Data Science Using SAS Open Source Integration [poster] |
Serena Faruque,
Stijn Rogiers |
source
video |
1 |
| PHUSE EU |
2021 |
Data Engineering - An Emerging Skill for Today's Statistical Programmers [presentation] |
Axel Muehlig,
Sangeeta Bhattacharya |
source
video |
18 |
| PHUSE EU |
2021 |
Data-driven Decisions: How an Increase in Data Demand is Driving the Creation of New Platforms Focused on Non-data Natives [presentation] |
Trevor Standish |
source
video |
10 |
| PHUSE EU |
2021 |
EMA Panel Discussion: What Might the Future Landscape of Submitting Data Look Like in 2025 ? [presentation] |
Eftychia-Eirini Psarelli,
Jesper Kjær |
source |
21 |
| PHUSE EU |
2021 |
Engineering an MDR of the Future [presentation] |
Ali Dootson,
Mike Grove |
source
video |
19 |
| PHUSE EU |
2021 |
Hey, Data Scientist: Are You Following the Rules and Your Conscience? [presentation] |
Lisa Brooks,
Dhananjay Chhatre |
source
video |
22 |
| PHUSE EU |
2021 |
How to Grow as a Programmer in the Pharmaceutical Industry [presentation] |
Julie Barré |
source
video |
22 |
| PHUSE EU |
2021 |
Integrated Summary of Safety and Efficacy Production Strategies |
Navneet Agnihotri,
Sumit Pratap Pradhan |
source
video
presentation source |
9 |
| PHUSE EU |
2021 |
Methods and Challenges of R Validation for Regulatory Submission Analysis [presentation] |
Parvee Kumar |
source
video |
14 |
| PHUSE EU |
2021 |
New Insights Through Cross-portfolio Risk Analysis [presentation] |
Abdollahi Rouhollah,
Julian Ortiz |
source
video |
17 |
| PHUSE EU |
2021 |
New Starters Session: The Secret Sauce to Start in Our Industry [presentation] |
Amritpal Singh,
Lucie Bowden |
source |
5 |
| PHUSE EU |
2021 |
New Starters Session: The Secret Sauce to Start in Our Industry [presentation] |
Amritpal Singh,
Lucie Bowden |
source |
10 |
| PHUSE EU |
2021 |
New Starters Session: The Secret Sauce to Start in Our Industry [presentation] |
Amritpal Singh,
Lucie Bowden |
source |
7 |
| PHUSE EU |
2021 |
New Starters Session: The Secret Sauce to Start in Our Industry [presentation] |
Amritpal Singh,
Lucie Bowden |
source |
11 |
| PHUSE EU |
2021 |
Preparing PK/PD ADaM Datasets and eCRT Data Package for FDA Submission |
Junying Zhang |
source
video
presentation source |
11 |
| PHUSE EU |
2021 |
PROC MIXED: A Complicated Procedure in Simple Words [presentation] |
Kateryna Fedoryshyna |
source
video |
21 |
| PHUSE EU |
2021 |
Programming Infrastructure to Automate Process Flow for CSS [presentation] |
Archana Nayak,
Salvatore Saporito |
source
video |
22 |
| PHUSE EU |
2021 |
Programming Techniques to Enhance the Presentation of Forest Plot with SAS 9.4 [presentation] |
Zhen (Laura) Li |
source
video |
18 |
| PHUSE EU |
2021 |
Software Demonstration: Aspire "Out of this World" Demo - Sponsored by d-wise [presentation] |
Andy Ratcliffe |
source |
44 |
| PHUSE EU |
2021 |
Software Demonstration: Unlocking Value from Structured Clinical Trial Data - Sponsored by Privacy Analytics [presentation] |
Thomasin Element |
source |
18 |
| PHUSE EU |
2021 |
Software Evolutions are Inevitable: Phase Your Coding evolution to Modern Clinical Trial Analytics by Using both Old/New Techniques in a Modern SAS Platform [presentation] |
Olivier Bouchard,
Pritesh Desai |
source
video |
19 |
| PHUSE EU |
2021 |
Studyathons: A New Way of Organising and Promoting Multidisciplinary Collaborations in Biomedical Open Science [presentation] |
Julia Kurps,
Maria Escala-Garcia |
source
video |
22 |
| PHUSE EU |
2021 |
The AstraZeneca Data Automation Team: Future-proofing Programming Teams to Meet Tomorrow's Challenges [poster] |
Ruhul Amin,
Tony Allen |
source
video |
1 |
| PHUSE EU |
2021 |
The Concept of IoT - The Next Generation of Statistical Computing Platform [presentation] |
Huadan Li,
Zhiping Yan |
source
video |
20 |
| PHUSE EU |
2021 |
The Last Mile of Analytics: Turn Your SAS Programs and Models into Interactive and 'Shiny' Apps [presentation] |
Dragos Coles,
Mark Lambrecht |
source
video |
15 |
| PHUSE EU |
2021 |
Tips and Tricks for Being More Productive with SAS Studio [presentation] |
Andy Bayliss |
source
video |
32 |
| PHUSE EU |
2021 |
Visualising Knowledge Graphs: Information Solution or Ball of Confusion? [presentation] |
Tim P. Williams |
source
video |
57 |
| SESUG |
2021 |
Asking the Right Questions: Designing Surveys to Produce Valid and Reliable Results |
Barbara B. Okerson |
source |
7 |
| SESUG |
2021 |
Back to Basics: Running an Analysis from Data to Refinement in SAS |
Deanna Naomi Schreiber-Gregory |
source |
21 |
| SESUG |
2021 |
Developing Ethical Data Use and Users |
Kelly D. Smith |
source |
7 |
| SESUG |
2021 |
Exploring the Skills Needed by the Data Scientist |
Kirk Paul Lafler |
source |
7 |
| SESUG |
2021 |
Statistical Test Selector (STS) For Researchers |
Kannan Deivasigamani,
Douglas Lunsford |
source |
11 |
| SESUG |
2021 |
Ten Rules for Better Charts, Figures and Visuals |
Kirk Paul Lafler |
source |
19 |
| PHUSE US |
2021 |
AI as a Service (AIaaS) in the RWD/RWE Space [presentation] |
Aaron Clark,
Himanshu Pandya |
source
video |
21 |
| PHUSE US |
2021 |
Automation of Patient Narratives Using Natural Language Generation [presentation] |
Sam Tomioka,
Shiva Katepalli |
source
video |
16 |
| PHUSE US |
2021 |
Building an SCE that Users Want to Use [presentation] |
Alastair Scarlett,
Chris Decker |
source
video |
9 |
| PHUSE US |
2021 |
Commercially Confidential Information in clinical data publishing [presentation] |
Parvee Kumar |
source
video |
17 |
| PHUSE US |
2021 |
Confused with PROC MIXED? Find Out What is the Best Model |
Savithri Jajam,
Vamshi Matta |
source
video
presentation source |
7 |
| PHUSE US |
2021 |
Demographic and Socio-economic Disparities in Preference to Getting Vaccinated by the Flu Shot versus the Flu Spray in the United States |
Swapna Ambati |
source
video
presentation source |
12 |
| PHUSE US |
2021 |
DSc Panel Discussion: How Data Scientists are Transforming the Biometrics Organization [presentation] |
Asha Mahesh,
Christopher J. Colangelo |
source
video |
9 |
| PHUSE US |
2021 |
Leadership Presentations: LE01: The Power of Three [presentation] |
Alberto Montironi,
Ryan Krause |
source |
15 |
| PHUSE US |
2021 |
Leadership Presentations: LE06: One Sprint at a Time - Agile Transformation in Clinical Research [presentation] |
Aman Bahl,
Steve Benjamin |
source |
17 |
| PHUSE US |
2021 |
Leveraging Standard Analytics in Central Monitoring: The Good, The Bad, & The Ugly [presentation] |
Angela Geiger,
Arianna Galli |
source
video |
20 |
| PHUSE US |
2021 |
Next Evolution Step(s) for Statistical Programmers: "Clinical Data Scientist" or "Clinical Data Analytics Engineer"? [presentation] |
Amar Mahidadia,
Sascha Ahrweiler |
source
video |
16 |
| PHUSE US |
2021 |
Open APIs and Open Source for Open Minds [presentation] |
Sven Prasse |
source
video |
19 |
| PHUSE US |
2021 |
Planning and Execution of Real-world Data Evidence Analysis |
Nicole Thorne,
Ramesh Sundaram |
source
video
presentation source |
6 |
| PHUSE US |
2021 |
Python in Healthcare: Coding the Future of Medicine [presentation] |
Swetha Mandava |
source
video |
26 |
| PHUSE US |
2021 |
R Shiny Application for the PHUSE Open Data Repository [presentation] |
Hanming Tu |
source
video |
15 |
| PHUSE US |
2021 |
Real-Time Clinical Trial Analytics Using Automation with IBM Clinical, Medidata Rave and Datacise [presentation] |
Aditya Gadiko,
Christopher C. Hurley |
source
video |
7 |
| PHUSE US |
2021 |
Scientific Listening: Content Analysis for Online Discussion of Bipolar Disorder [presentation] |
Bowen Lu |
source
video |
13 |
| PHUSE US |
2021 |
Software Demonstration: SD13: RStudio Pharma Updates [presentation] |
Sean Lopp |
source |
12 |
| PHUSE US |
2021 |
Using Real-world Data in Supporting Health Authority Submission [presentation] |
Ruoying Fang,
Shuang Zhang |
source
video |
26 |
| PHUSE US |
2021 |
Visual Programming for ADaM Derivation [presentation] |
Clara Beck,
Robert Adams |
source
video |
33 |
| PharmaSUG |
2021 |
"Packages" in R for Clinical Data Analysis, Let's Demystify |
Nagalakshmi Kudipudi |
source |
8 |
| PharmaSUG |
2021 |
A Programmer's Experience Researching Real-World Evidence (RWE) COVID-19 Data |
Ginger Barlow |
source |
5 |
| PharmaSUG |
2021 |
A TransCelerate Initiative - how can you modernize your statistical environment? |
Vincent J. Amoruccio,
Min Lee,
Daniel Woodie |
source |
16 |
| PharmaSUG |
2021 |
ADaM Implementation Guide for Medical Devices |
Julia Yang,
Silvia Faini,
Karin LaPann |
source |
11 |
| PharmaSUG |
2021 |
Agile Project Management in Analysis and Reporting of Late Stage Clinical Trial |
Sarad Nepal,
Uday Preetham Palukuru,
Peikun Wu,
Madhusudhan Ginnaram,
Ruchitbhai Patel,
Abhilash Chimbirithy |
source |
11 |
| PharmaSUG |
2021 |
Analysis and Reporting in Regulated Clinical Trial Environment using R |
Peikun Wu,
Uday Preetham Palukuru,
Yiwen Luo,
Sarad Nepal,
Yilong Zhang |
source |
11 |
| PharmaSUG |
2021 |
Back to Basics: Running an Analysis from Data to Refinement in SAS |
Deanna Naomi Schreiber-Gregory |
source |
21 |
| PharmaSUG |
2021 |
Bookdown and Blogdown: Using R packages to document and communicate new processes to Clinical Programming |
Benjamin Straub |
source |
11 |
| PharmaSUG |
2021 |
Delight the Customer using agile transformation in Clinical Research |
Aman Bahl,
Steve Benjamin,
Hrideep Antony |
source |
9 |
| PharmaSUG |
2021 |
Evaluating anthropometric growth endpoints with Z-Scores and Percentiles |
Snehal Sanas,
Pradeep Umapathi |
source |
11 |
| PharmaSUG |
2021 |
Generating .xpt files with SAS, R and Python |
YuTing Tian,
Todd Case |
source |
11 |
| PharmaSUG |
2021 |
How I became a Machine Learning Engineer from a Statistical Programmer |
Kevin Lee |
source |
4 |
| PharmaSUG |
2021 |
How to handle decision making in the CRO / sponsor relationship in matters that require expertise |
Sarah McLaughlin |
source |
3 |
| PharmaSUG |
2021 |
Life After Drug Approval... What Programmers Need to Know About REMS |
Cara Lacson,
Carol Matthews |
source |
11 |
| PharmaSUG |
2021 |
Macro Development from Design to Implementation Applied to Occurrence Data Frequency Analysis |
Chengxin Li,
Michael Pannucci,
Toshio Kimura |
source |
9 |
| PharmaSUG |
2021 |
Making Your SAS Results More Meaningful with Color |
Kirk Paul Lafler |
source |
19 |
| PharmaSUG |
2021 |
R Reproducibility Best Practices for Pharma |
Philip Bowsher,
Sean Lopp |
source |
4 |
| PharmaSUG |
2021 |
Untangling the Knot - Implementing Analysis Results Standards (Using SAS) |
Hansjörg Frenzel |
source |
10 |
| PharmaSUG |
2021 |
Why Data Scientists need leadership skills? Story of Cross-Value Chain Data Utilization Project |
Yura Suzuki,
Yuichi Koretaka,
Ryo Kiguchi,
Yoshitake Kitanishi |
source |
8 |
| SGF |
2021 |
Back to Basics: Running an Analysis from Data to Refinement in SAS |
Deanna Naomi Schreiber-Gregory |
source
presentation |
20 |
| SGF |
2021 |
Bridging the Gap Between Legacy SAS and SAS Viya at the Centers for Medicare and Medicaid (CMS) |
Richard Andrews,
Manuel Figallo-Monge,
Kevin Boone,
Prakash Subramanian,
Logan Perry |
source |
21 |
| SGF |
2021 |
Deep Learning to Classify Adverse Events from Patient Narratives [presentation] |
Qais Hatim,
Tom Sabo |
source |
19 |
| SGF |
2021 |
Generating .xpt files with SAS, R and Python |
Todd Case |
source |
11 |
| SGF |
2021 |
Haste Makes Waste: Don't Ruin Your Reputation With Hasty Regression |
Steven C. Myers |
source
presentation
sas |
39 |
| SGF |
2021 |
Large-scale demand forecasting for e-commerce retailer using SAS Forecast Studio: A Case Study |
Ajay Kumar Mishra,
Mohak Narkhede,
Padmanabha Chandu Saladi |
source |
9 |
| SGF |
2021 |
Making Text Analytics More Approachable |
Sundaresh Sankaran |
source |
9 |
| SGF |
2021 |
Tips for Providing Effective and Budget-Friendly SAS Development in a Remote Environment |
Kelly D. Smith |
source
presentation |
9 |
| PHUSE EU |
2020 |
A Collaborative Approach to Analysis Standards [presentation] |
Margie Merlino,
Marleen Nijs |
source
video |
22 |
| PHUSE EU |
2020 |
Advancing SDTM Annotation Through Automation [presentation] |
Anja Kreis,
Wolfgang Rohnert |
source
video |
20 |
| PHUSE EU |
2020 |
Data Integrity & Standards in the Clinical Data Pipeline [presentation] |
Mark Wheeldon,
Raj Indupuri |
source
video |
30 |
| PHUSE EU |
2020 |
Deploying Machine Learning in Data Management [presentation] |
Sheila Rocchio |
source
video |
11 |
| PHUSE EU |
2020 |
Digital Data Flow - A Solution for Study Start-up and Amendments [presentation] |
Palanipandiyan Chokkalingam,
Srinivasan Mahalingam |
source
video |
22 |
| PHUSE EU |
2020 |
Drug Safety and Efficacy - Smart Regulatory Solution [presentation] |
Haider Ali,
Rhim Suh Ngu'eh Shu |
source
video |
17 |
| PHUSE EU |
2020 |
Generation of Statistical Analysis Programs Made Easy (and Transparently) [poster] |
Adrian Czaban,
Niels Zeuthen |
source
video |
1 |
| PHUSE EU |
2020 |
How I Changed the Habits of a Lifetime with SAS Studio and SAS Viya [presentation] |
Andy Bayliss |
source
video |
41 |
| PHUSE EU |
2020 |
How I Learnt Python in 15 Days |
Vikas Dhongde |
source
video
presentation source |
4 |
| PHUSE EU |
2020 |
Improve Programming and Traceability with Datasets for Statistical Analysis Results |
Henning Pontoppidan Föh,
Jeppe Juul |
source
video
presentation source |
4 |
| PHUSE EU |
2020 |
Innovation in Exploratory/Regulatory Clinical Trial Analyses [presentation] |
Tadeusz Lewandowski |
source
video |
31 |
| PHUSE EU |
2020 |
Last Mile Problem to Manage Data Transformation for Analysis & Reporting [presentation] |
Deven Babre,
Rajaram Venkatesan |
source
video |
19 |
| PHUSE EU |
2020 |
Leading Innovation and Change via Olympic Goals [presentation] |
Robin Koeger,
Ross Farrugia |
source
video |
14 |
| PHUSE EU |
2020 |
Let CDISC Be |
Roxane Debrus,
Silvia Faini |
source
video
presentation source |
8 |
| PHUSE EU |
2020 |
One Boy's Dream: Hitting a Homerun in the Bottom of the Ninth Inning [presentation] |
Carey G. Smoak |
source
video |
23 |
| PHUSE EU |
2020 |
Patient Insights and Real-world Data from Social Media [presentation] |
Luisa Regenold,
Soundarya Palanisamy |
source
video |
28 |
| PHUSE EU |
2020 |
SAS Studio - Time to Move on from Display Manager and Enterprise Guide [presentation] |
Andy Bayliss |
source
video |
18 |
| PHUSE EU |
2020 |
Teaching an Old Dog New Tricks with Python [presentation] |
Donald Paterson |
source
video |
34 |
| PHUSE EU |
2020 |
The Evolution of Statistical Computing Environments: Time for a Quantum Leap? [presentation] |
Ali Dootson |
source
video |
22 |
| PHUSE EU |
2020 |
The Validation of Open-source Tools for Clinical Statistics and Programming [presentation] |
Ali Dootson,
Richard Pugh |
source
video |
21 |
| PHUSE EU |
2020 |
Understanding the Spread of COVID-19 in the United States Using Topology and Machine Learning for Time Series |
Iryna Kotenko,
Kostiantyn Drach |
source
video
presentation source |
32 |
| PHUSE EU |
2020 |
Use Cases of Google Sheets in Programming Applications [presentation] |
Carina Hillenbach |
source
video |
16 |
| PHUSE EU |
2020 |
Using R from End to End: CDISC SDTM and ADaM into .xpt and Output Generation [presentation] |
Antonio Rodríguez Contestí |
source
video |
46 |
| PHUSE EU |
2020 |
Using Software Development Principles and Tools to Create an R Package for Data Analysis Optimisation [presentation] |
Emanuil Markov,
Svetomir Hitov |
source
video |
19 |
| PHUSE EU |
2020 |
Visualisation of Risk Indicators Using the Shiny App [presentation] |
Kadriye Kaplan |
source
video |
10 |
| SESUG |
2020 |
Exploring Professional Data Science / Analytics Skills |
Kirk Paul Lafler |
source |
6 |
| SESUG |
2020 |
Making Your SAS Results More Meaningful with Color |
Kirk Paul Lafler |
source |
20 |
| SGF |
2020 |
Apply the Key Ideas from Andrew Ng's Machine Learning Certification (Coursera) in SAS Viya |
Petri Roine |
source |
9 |
| SGF |
2020 |
Automation in SAS Visual Data Mining and Machine Learning |
Wendy Czika |
source |
26 |
| SGF |
2020 |
CAS Sessions: Understanding Connection Options to Ensure Data Access Security |
Philip Hopkins |
source |
19 |
| SGF |
2020 |
Choose Your Own Adventure: Manage Model Development Via a Python Integrated Development Environment |
Jon Walker |
source |
17 |
| SGF |
2020 |
Enhancing Academic Teaching of Data Science with SAS Viya for Learners |
Stefan Dimitrov Stoyanov |
source |
30 |
| SGF |
2020 |
Expedite Analytics Deliver and Empowerment with a Common Analytics Base Table |
Jennifer L. Nenadic |
source |
11 |
| SGF |
2020 |
From Santiago to the Spirit Lake Nation: 30 Things I Learned in 30 Years as a Statistical Consultant |
AnnMaria De Mars |
source |
20 |
| SGF |
2020 |
How SAS Viya Provides a Way to Deliver Analytics to Everyone: Image Classification Examples |
Pavel Rogatch |
source |
5 |
| SGF |
2020 |
Language Lessons for Data-Driven Decisions: Achieving Data Literacy |
Emma Warrillow |
source |
8 |
| SGF |
2020 |
Measuring Analytic Performance in Financial Terms for Executives |
Tho H. Nguyen |
source |
5 |
| SGF |
2020 |
Open Source Python & R Lang on our SAS Shared Grid (SSG) |
Thomas Ball |
source |
5 |
| SGF |
2020 |
SAS BI Platform to Improve Use of Analytics in Higher Education: Do the Stats Match the Intent? |
Sean W. Mulvenon |
source |
7 |
| SGF |
2020 |
Show Me the Money! Preparing Economics Students for Data Science Careers |
Steven C. Myers |
source |
19 |
| SGF |
2020 |
Solving Health Problems on the Academic Frontier: Training Students to Use SAS Through Research |
Charlotte Baker |
source |
5 |
| SGF |
2020 |
Statistical Programming in the Pharmaceutical Industry: Advancing and Accelerating Drug Development |
Harper Forbes |
source |
10 |
| SGF |
2020 |
Transdermal Medicine - Challenges and Solutions with SAS |
Marina Komaroff |
source |
14 |
| SGF |
2020 |
Using Jupyter to Boost Your Data Science Workflow |
Hunter Glanz |
source |
12 |
| SGF |
2020 |
Using Lag and Other Function in SAS to Create Final Datasets Temperature Study |
Abbas S. Tavakoli |
source |
14 |
| SGF |
2020 |
Using SAS and R Integration to Manage and Create a Multilevel Complex Database: A Case Study of the U. S. Department of Defense Military Health System Data Repository |
Akhtar Hossain,
Nikki R. Wooten,
Laura A. Hopkins |
source |
6 |
| SGF |
2020 |
Using SAS9API and R to Create Violin Plots, Interactive 3D Plots, and a Shiny App for SAS Data Sets [presentation] |
Olga Pavlova |
source |
7 |
| SGF |
2020 |
What's New in SAS Visual Data Mining and Machine Learning: From a Programmer's Perspective |
Tao Wang |
source |
13 |
| SGF |
2020 |
Writing Data Quality rules using SAS Meta-programming [presentation] |
Shreyas Dalvi |
source |
7 |
| PharmaSUG |
2020 |
A Brief Introduction to Performing Statistical Analysis in SAS, R & Python |
Erica Goodrich,
Daniel Sturgeon |
source |
22 |
| PharmaSUG |
2020 |
A Single, Centralized, Biometrics Team Focused Collaboration System for Analysis Projects |
Chris Hardwick,
Justin Slattery,
Hans Gutknecht |
source |
11 |
| PharmaSUG |
2020 |
An Effective Management Approach for a First-Time Study Lead |
Himanshu Patel,
Jeff Xia |
source |
10 |
| PharmaSUG |
2020 |
Building a Strong Remote Working Culture - Statistical Programmers Viewpoint |
Ravi Kankipati,
Prasanna Sondur |
source |
4 |
| PharmaSUG |
2020 |
Effective Exposure-Response Data Visualization and Report by Combining the Power of R , SAS programming and VBScript |
Shuozhi Zuo,
Hong Yan |
source |
11 |
| PharmaSUG |
2020 |
Metadata-driven Modular Macro Design for SDTM and ADaM |
Ellen (Zihui) Lin,
Aditya Tella,
Yeshashwini Chenna,
Michael Hagendoorn |
source |
9 |
| PharmaSUG |
2020 |
Oncology Graphs-Creation (Using SAS and R), Interpretation and QA |
Taniya Muliyil |
source |
10 |
| PharmaSUG |
2020 |
PROC Future Proof; |
Amy Gillespie,
Susan Kramlik,
Suhas R. Sanjee |
source |
8 |
| PharmaSUG |
2020 |
RStats: A R-Shiny application for statistical analysis |
Sean Yang,
Hrideep Antony,
Aman Bahl |
source |
8 |
| PharmaSUG |
2020 |
Standardised MedDRA Queries (SMQs): Programmers Approach from Statistical Analysis Plan (SAP) to Analysis Dataset and Reporting |
Sumit Pratap Pradhan |
source |
18 |
| PharmaSUG |
2020 |
Why Are There So Many ADaM Documents, and How Do I Know Which to Use? |
Sandra Minjoe |
source |
10 |
| PHUSE US |
2020 |
A Programmer's Journey through the BIMO Submission Process |
Raghavender Ranga |
source
presentation source |
12 |
| PHUSE US |
2020 |
All about versioning - an intro into Distributed Version Control |
Mark Bynens |
source
presentation source |
11 |
| PHUSE US |
2020 |
Best Practices for Building and Testing Interactive Web Applications in R with Shiny |
Kelly O'Briant |
source |
5 |
| PHUSE US |
2020 |
Big Data Analytics with JuliaDB |
Vitali Marenny |
source
presentation source |
6 |
| PHUSE US |
2020 |
Custom Monitoring Solutions in R: How to Create Powerful Dashboards Using R Markdown |
Kelly O'Briant |
source |
5 |
| PHUSE US |
2020 |
Data Science Project (Educating for the Future Working Group) |
Aldir Medeiros Filho,
Sascha Ahrweiler |
source
presentation source |
10 |
| PHUSE US |
2020 |
Data Wrangling - Combining and Restructuring QS-related ADaM Datasets for Pathway Predictive Modeling |
Stanley Brill |
source
poster source |
7 |
| PHUSE US |
2020 |
Dual Roles: I'm not just a programmer! |
Laura Williams,
Hunter Vega |
source
presentation source |
5 |
| PHUSE US |
2020 |
Efficacy ADaMs in Oncology - Step by Step (Dataset by Dataset) |
Ilya Krivelevich,
Ran Xie |
source
presentation source |
8 |
| PHUSE US |
2020 |
End-to-End Interactive TLF Using R Shiny |
Rohit Banga |
source
presentation source |
13 |
| PHUSE US |
2020 |
Evolution of Data: From extraction to visualization |
Ashish Kumar |
source
presentation source |
11 |
| PHUSE US |
2020 |
Feedback to Feed Back |
Ankur Mathur,
Harper Forbes |
source
presentation source |
5 |
| PHUSE US |
2020 |
Good Cooperation Between SAS and R for Regulatory Submission |
Jingyuan Chen |
source
presentation source |
8 |
| PHUSE US |
2020 |
How GSK Tech is Democratizing Data Science |
Pragathi Venkata |
source
presentation source |
7 |
| PHUSE US |
2020 |
Integration of Biomarkers Data in Clinical Trials |
Prakash Dev |
source
presentation source |
5 |
| PHUSE US |
2020 |
Is R language reliable and efficient tool for programming SAS datasets or just art for art's sake? |
Piotr Podlewski |
source
presentation source |
9 |
| PHUSE US |
2020 |
Lab Master List File Makes Easy |
Clio Wu |
source
presentation source |
7 |
| PHUSE US |
2020 |
Let Us Trace Back to the Beginning from the End |
Madhusudhan Reddy Papasani,
Swathi Kotla |
source
presentation source |
12 |
| PHUSE US |
2020 |
Open Source Technologies in Clinical Research |
Bruce Wienckowski,
Michael S Rimler |
source
presentation source |
7 |
| PHUSE US |
2020 |
Population PK Dataset: Basic Concepts and Challenges from the Perspective of a SAS Programmer |
Namrata Pokhrel |
source
presentation source |
12 |
| PHUSE US |
2020 |
R & Python for Clinical Workflows |
Philip Bowsher |
source |
13 |
| PHUSE US |
2020 |
R syntax for SAS programmers |
Max Cherny |
source
presentation source |
12 |
| PHUSE US |
2020 |
Reproducible Open-source Environments for Advance Analytics |
Sean Lopp |
source
presentation source |
3 |
| PHUSE US |
2020 |
Smart, Digital Analysis & Reporting (A&R) Environments: They Are Upon Us |
Christopher J. Colangelo |
source
presentation source |
8 |
| PHUSE US |
2020 |
Statistical Analysis in an Oncology Study for PCWG3 Patients [poster] |
Tony Tian |
source |
1 |
| PHUSE US |
2020 |
Visualizing clinical operational metrics to enable decision-making and accountability |
Michael Gonzales |
source
presentation source |
11 |
| PHUSE EU |
2019 |
All about versioning - an intro into Distributed Version Control |
Mark Bynens |
source
presentation source |
12 |
| PHUSE EU |
2019 |
An Introduction to Python: The SAS Programmer's Guide |
Bradley Harris |
source
presentation source |
8 |
| PHUSE EU |
2019 |
Automated Review of Metadata Standards, Data Checks and Trend Visualisation |
Giuseppe Di Monaco |
source
presentation source |
9 |
| PHUSE EU |
2019 |
Educating for the Future: Data Engineering Techniques |
Guy R. Garrett |
source
presentation source |
10 |
| PHUSE EU |
2019 |
Mistakes Managers Make While Managing Data Scientists that You Will Want to Identify and Prevent |
James R. Johnson |
source
presentation source |
7 |
| PHUSE EU |
2019 |
Optimise PRO Data Analysis with an Interactive Approach |
Tadeusz Lewandowski |
source
presentation source |
9 |
| PHUSE EU |
2019 |
Pharmacokinetic and Statistical Considerations in First-in-Human Clinical Trials |
Joanna Magielse |
source
presentation source |
4 |
| PHUSE EU |
2019 |
Quality Control and Validation - More Than Just PROC COMPARE |
Evgeny Starostin |
source
poster source |
7 |
| PHUSE EU |
2019 |
R or Python? Dilemma, Dilemma |
Elsa Lozachmeur,
Nicolas Dupuis |
source
presentation source |
18 |
| PHUSE EU |
2019 |
Sub-population Detection Using Graph-based Machine Learning |
Sergey Glushakov,
Kostiantyn Drach |
source |
28 |
| SESUG |
2019 |
Clarifying the Assessment Picture: Defined Metrics and Programming Choices in SAS Coding |
Jerry Landry,
Kelly D. Smith |
source |
6 |
| SESUG |
2019 |
ePRO: A View from Statistical Programmer |
Vijetha Kode,
Saigovind Chenna |
source |
18 |
| SESUG |
2019 |
Macros for Neural Network Modeling |
Ross Bettinger |
source |
23 |
| SESUG |
2019 |
Making Your SAS Results More Meaningful with Color |
Kirk Paul Lafler |
source |
20 |
| SESUG |
2019 |
Probability Plots for Exploratory Data Analysis |
Dennis J. Beal,
Oak Ridge |
source |
8 |
| SCSUG |
2019 |
Explore your data before you rush to analysis, you will thank me later: explorations in cross section data |
Steven C. Myers |
source |
28 |
| SCSUG |
2019 |
Making Your SAS Results More Meaningful with Color |
Kirk Paul Lafler |
source |
20 |
| MWSUG |
2019 |
Deploying SAS Viya Docker images to the cloud - a step by step guide |
Alan Zablocki |
|
25 |
| MWSUG |
2019 |
Explore your data before you rush to analysis, you will thank me later: explorations in cross section data |
Steven C. Myers |
|
28 |
| MWSUG |
2019 |
Legislative Action on Human Trafficking: Towards a Data-Driven Policy |
David J. Corliss |
|
9 |
| MWSUG |
2019 |
No Wrong Door |
Jack N. Shoemaker |
|
8 |
| MWSUG |
2019 |
Why Admitted Students Opt-out of College Enrollment? |
Manasi Murde,
Miriam McGaugh |
|
13 |
| WUSS |
2019 |
Statistical Power Calculations Using SAS Software |
Russell M. Lavery |
source |
18 |
| WUSS |
2019 |
USING JUPYTER TO TAKE YOUR DATA SCIENCE WORKFLOW TO THE NEXT LEVEL |
Hunter Glanz |
source |
12 |
| PharmaSUG |
2019 |
A Practical Guide to the Issues Summary in the Data Conformance Summary of Reviewer's Guides |
Gary E. Moore |
source |
15 |
| PharmaSUG |
2019 |
Best Practices for ISS/ISE Dataset Development |
Bharath Donthi,
Lingjiao Qi |
source |
9 |
| PharmaSUG |
2019 |
China NMPA (National Medical Products Administration) reform and new regulations/guidelines/requirements |
Yi Yang |
source |
11 |
| PharmaSUG |
2019 |
Considering Job Changes in an Ever-Changing Environment |
Kathy Bradrick,
Ed Slezinger |
source |
6 |
| PharmaSUG |
2019 |
Do-It-Yourself CDISC! A Case Study of Westat's Successful Implementation of CDISC Standards on a Fixed Budget |
Richard M. Mitchell,
Rachel Brown,
Jennifer K. Fulton,
Stephen Black,
Marie Byrd Alexander |
source |
6 |
| PharmaSUG |
2019 |
Flagging On-Treatment Events in a Study with Multiple Treatment Periods |
David W. Franklin |
source |
4 |
| PharmaSUG |
2019 |
Hands-on Training for Machine Learning Programming |
Kevin Lee |
source |
12 |
| PharmaSUG |
2019 |
Improving the Relationship between Statisticians and Programmers in Clinical Trial Studies |
Mai Ngo,
Mary Grovesteen,
Vaughn Eason |
source |
8 |
| PharmaSUG |
2019 |
Making Lab Toxicity Tables Less Toxic on Your Brain |
Lindsey Xie,
Jinlin Wang,
Jennifer Sun,
Rita Lai,
Richann J. Watson |
source |
13 |
| PharmaSUG |
2019 |
SHIONOGI Global SAS System Renewal Project - How to Improve Statistical Programming Platform |
Yura Suzuki,
Yoshimi Ishida,
Malla Reddy Boda,
Yoshitake Kitanishi |
source |
10 |
| PharmaSUG |
2019 |
Statistical Programming Roles - Time to Reevaluate Job Profiles & Career Ladders |
Vijay Moolaveesala,
Ajay Gupta |
source |
4 |
| PharmaSUG |
2019 |
The Anatomy of Clinical Trials Data: A Beginner's Guide |
Venky Chakravarthy |
source |
14 |
| PharmaSUG |
2019 |
The Power of Data Visualization in R |
Oleksandr Babych |
source |
21 |
| PharmaSUG |
2019 |
This Paper focuses on CDISC Questionnaires, Ratings and Scales (QRS) supplements and types of FDA Clinical Outcome Assessments |
Shrishaila Patil |
source |
10 |
| PharmaSUG |
2019 |
Useful SAS techniques in Efficacy Analysis for Oncology studies |
Joy Zeng |
source |
21 |
| PharmaSUG |
2019 |
Why we should learn Python |
Kevin Lee |
source |
11 |
| SGF |
2019 |
5W1H Method: SAS Viya as Your Cloud Analytics Platform? Who, What, When, Where, Why, and How |
Daniel Hatton |
source |
10 |
| SGF |
2019 |
A Complete Introduction to SASPy and Jupyter Notebooks |
Jason Phillips |
source |
9 |
| SGF |
2019 |
A Practical Guide to Responsive Reactive Design Using SAS Visual Analytics |
Elliot Inman |
source |
18 |
| SGF |
2019 |
AI is Coming for Your BI: Automated Analysis in SAS Visual Analytics |
Rick Styll |
source |
19 |
| SGF |
2019 |
Collaboration Calibration: How SAS Data Scientists Collaborate Effectively Using SAS Viya |
Weston McManus,
Allison Becker |
source |
11 |
| SGF |
2019 |
Combating Fraud and Financial Crime Effectively by Empowering Data Scientists Using SAS Viya |
Steve Overton |
source |
10 |
| SGF |
2019 |
Create True Load Sharing Facility Batch Job Submission Capability on SAS Enterprise Guide in a SAS Grid [presentation] |
Adam Hendricks,
Derek Grittmann |
source |
14 |
| SGF |
2019 |
Data Preparation in the Analytical Life Cycle |
Ivor G. Moan |
source |
8 |
| SGF |
2019 |
Deploying Models Using SAS and Open Source |
Jared Dean |
source |
10 |
| SGF |
2019 |
Developing a Credit Risk Model Using SAS |
Amos Odeleye |
source |
16 |
| SGF |
2019 |
Don't Just Survive, Thrive! A Learning-Based Strategy for a Modern Organization Centered Around SAS |
Jovan Marjanovic |
source |
7 |
| SGF |
2019 |
Don't Let Complex Survey Data Get the Best of You! SAS Survey PROCs for Categorical Data Analysis |
Charlotte Baker |
source |
16 |
| SGF |
2019 |
Dynamic Call Center Simulation in SAS: Revamping the Business Resiliency Process at JPMorgan Chase |
Jay P. Carini,
Amy Pielow,
Joel C. Weaver |
source |
16 |
| SGF |
2019 |
How Access to STEM can Save the World |
Jennifer Sabourin,
Lucy Kosturko |
source |
8 |
| SGF |
2019 |
Identifying Partisanship in Media Articles |
Alexander Lobman,
Lohit Bhandari,
Ravi Josyula,
Nhan Nguyen |
source |
7 |
| SGF |
2019 |
Interaction between SAS and Python for Data Handling and Visualization |
Yohei Takanami |
source |
22 |
| SGF |
2019 |
Kustomizing Your Viya Engine Using SAS Studio Custom Tasks and D3.js |
Elliot Inman,
Ryan West,
Olivia Wright |
source |
16 |
| SGF |
2019 |
Learning Data Science with SAS University Edition and JupyterLab |
Brian R. Gaines |
source |
17 |
| SGF |
2019 |
Machine Learning and Predictive Analytics in SAS Enterprise Miner and SAS/STAT Software |
David Richard Cutler |
source |
21 |
| SGF |
2019 |
Machine Learning for Effective Surveillance with SAS Adaptive Learning and Intelligent Agent System |
Rory MacKenzie |
source |
14 |
| SGF |
2019 |
Make SAS Viya Realize Strategic Data Science - Data Governance, AI Platform and AI SAS Programmer |
Ryo Kiguchi,
Katsunari Hirano,
Yoshitake Kitanishi |
source |
8 |
| SGF |
2019 |
Measuring Analytic Performance in Financial Terms for Executives |
Kenneth Pikulik |
source |
5 |
| SGF |
2019 |
New to SAS? Helpful hints for developing your own professional development plan |
Kelly D. Smith |
source |
12 |
| SGF |
2019 |
Overcoming the Blockers: Analytics Adoption Strategies Used by Successful Organizations |
Patricia S. Aanderud,
Reid Baughman,
Ken Matz,
Chris St. Jeor |
source |
16 |
| SGF |
2019 |
Review and Comparing (Analyzing) Relationship between Teacher Judgment and Student Performance in North Carolina |
Sareh Meshkinfam,
Julie S. Ivy,
Amy C. Reamer |
source |
15 |
| SGF |
2019 |
SAS Viya: Experience Gained through Multiple Installations and Implementations |
John Schmitz |
source |
14 |
| SGF |
2019 |
SF12v2 Health Scores for African Americans Using SAS in a Cluster-Randomized Community Trial [presentation] |
Thomas Joshua,
Lucy Marion,
Lovoria Williams,
Jane Garvin |
source |
10 |
| SGF |
2019 |
Stepping Up Your SAS Game with Jupyter Notebooks |
Hunter Glanz |
source |
12 |
| SGF |
2019 |
Stories from the Trenches: Tips and Techniques for Career Advancement from a SAS Industry Recruiter |
Molly Hall |
source |
15 |
| SGF |
2019 |
SWAT's it all about? SAS Viya for Python Users |
Carrie Foreman |
source |
18 |
| SGF |
2019 |
The "Why" and "How" of Teaching SAS to High School Students |
Jennifer Richards |
source |
5 |
| SGF |
2019 |
The Categorical Might of PROC FREQ |
Jinson J. Erinjeri,
Saritha Bathi |
source |
18 |
| SGF |
2019 |
Using Proc Optigraph to Implement the Prize Collecting Traveling Salesman Problem in SAS |
Bryan Yockey,
Joe DeMaio |
source |
14 |
| SGF |
2019 |
Using SAS Viya to Implement Custom SAS Analytics in Python; A Cybersecurity Example |
Damian Herrick |
source |
12 |
| PHUSE US |
2019 |
2018 Clinical Data Landscape Survey |
James McDermott,
Guy R. Garrett |
source
presentation source |
12 |
| PHUSE US |
2019 |
A Future 'View' of Digital Data from Wearable Devices |
Daniel Schramek |
source
presentation source |
11 |
| PHUSE US |
2019 |
Data Visualization |
Anand Phulphagar |
source
presentation source |
8 |
| PHUSE US |
2019 |
How Do I Pick an R Package for My Clinical Workflow? |
Philip Bowsher |
source
presentation source |
18 |
| PHUSE US |
2019 |
Interactive Exploratory Analysis and Visualization for Late-phase Clinical Data |
Sheng-Wei Wang,
Casey Yang |
source
presentation source |
9 |
| PHUSE US |
2019 |
Interactive Monitoring of Hepatotoxicity |
Susan Duke |
source
presentation source |
10 |
| PHUSE US |
2019 |
Metadata-based Auto-Programming Process - Part 2: Map Human Language to SAS Code by Natural Language Processing (NLP) |
Sumesh Kalappurakal,
Harry Chen |
source
presentation source |
11 |
| PHUSE US |
2019 |
New Drug Development Paradigm [presentation] |
Francis Kendall,
Cytel |
source |
33 |
| PHUSE US |
2019 |
Optimize PRO Data Analysis with an Interactive Approach |
Xiangyun Wang,
Elisabeth Piault-Louis |
source
presentation source |
8 |
| PHUSE US |
2019 |
R Markdown for Reproducible Research |
Cole Arendt |
source
presentation source |
15 |
| PHUSE US |
2019 |
Submission of Software Programs to Regulatory Agencies |
Maria Dalton |
source
presentation source |
10 |
| SCSUG |
2018 |
Advanced Analytics Architecture at General Motors |
Joe Aarons |
source |
27 |
| SCSUG |
2018 |
Making Your SAS Results, Reports, Tables, Charts and Spreadsheets More Meaningful with Color |
Kirk Paul Lafler |
source |
20 |
| SCSUG |
2018 |
Visual Storytelling - The Art of Communicating Information with Graphics |
Kirk Paul Lafler |
source |
16 |
| PHUSE EU |
2018 |
2018 Clinical Data Landscape Survey |
James McDermott,
Dante Di Tommaso |
source
presentation source |
12 |
| PHUSE EU |
2018 |
Access Rights Management and Version Control in an Independent Programming Environment |
Christian Sachara,
Anke Grohl |
source
presentation source |
6 |
| PHUSE EU |
2018 |
An Efficient Way for Statistical Review Using RShiny Application |
Adarsh Nagare,
Sameer Bamnote |
source
presentation source |
9 |
| PHUSE EU |
2018 |
APESS: A Unified Methodology for the Development and Review of Quantitative Analysis SOPs |
Andy Richardson,
Anthony Rossinin |
source
presentation source |
7 |
| PHUSE EU |
2018 |
Data Engineering Project (Educating for the Future PHUSE Working Group) |
Guy R. Garrett,
Bev Hayes |
source
presentation source |
14 |
| PHUSE EU |
2018 |
Disruption Leads to Innovation: We Must Learn New Things! |
Chris Decker,
Ali Dootson |
source
presentation source |
8 |
| PHUSE EU |
2018 |
Handling Missing Data in Clinical Trials Using Topological Data Analysis |
Sergey Glushakov,
Andrey Rekalo |
source
presentation source |
10 |
| PHUSE EU |
2018 |
How to Write ADaM Specifications Like a Ninja |
Caroline Francis |
source
poster source |
5 |
| PHUSE EU |
2018 |
iGET it! Downloading Data from a Centralised Repository Using PROC HTTP |
Neville Cope |
source
presentation source |
7 |
| PHUSE EU |
2018 |
Implementation of a Metadata-based Approach to Statistical Planning, Analysis and Reporting |
Frank Freischlager,
Hanspeter Schnitzer |
source
presentation source |
7 |
| PHUSE EU |
2018 |
Implementation of Data Cut Off in Analysis of Clinical Trials |
Ann Croft |
source
presentation source |
13 |
| PHUSE EU |
2018 |
Lessons Learned for Successful e-Study Data Submission to the PMDA towards the End of the Transitional Period |
Takashi Kitahara,
Ayako Noda |
source
presentation source |
12 |
| PHUSE EU |
2018 |
Overlooked Tiny Numeric Representation Errors in SAS May Lead to Substantially Misleading p-Value |
Ying Zhou,
David Haryanto |
source
presentation source |
11 |
| PHUSE EU |
2018 |
SAS Life Science Analytical Framework (LSAF) in a Nutritional Clinical Research Setting |
Mickaël Hartweg,
Justine Morlet |
source
presentation source |
7 |
| PHUSE EU |
2018 |
Serious Adverse Events Identification: A Machine Learning Approach [presentation] |
Jingshu Liu,
Laura Katz |
source |
37 |
| PHUSE EU |
2018 |
The "CDISC Stupidario" (the CDISC Nonsense) |
Angelo Pinazzi |
source
poster source |
11 |
| PHUSE EU |
2018 |
The Generation Game - The X, Y and Z of Line Managing Clinical Data Scientists |
Diana Stuart |
source
presentation source |
5 |
| SESUG |
2018 |
The "Why" and "How" of Teaching SAS to High School Students |
Jennifer Richards |
source |
9 |
| SESUG |
2018 |
The Categorical Might of PROC FREQ |
Jinson J. Erinjeri,
Saritha Bathi |
source |
18 |
| SESUG |
2018 |
Utilization of SAS Input Statements for the Barell Injury Diagnosis Matrix to Categorize Senior Sports Injury by Body Region and Nature of Injury |
Body Region |
source |
4 |
| MWSUG |
2018 |
Computer Karma: Non-Monetary Benefits from Statistical And Information Technology Volunteer Work |
Brandy R. Sinco |
|
11 |
| MWSUG |
2018 |
Data For Good as a Community Service Project at Work |
David J. Corliss |
|
6 |
| MWSUG |
2018 |
Data-Driven Data Analysis |
Jack N. Shoemaker |
|
10 |
| MWSUG |
2018 |
Factors Responsible for Students' Enrollment at Oklahoma State University |
Parag Vilas Sasturkar |
|
6 |
| MWSUG |
2018 |
How to Succeed in Consulting |
Chuck Kincaid |
|
15 |
| MWSUG |
2018 |
Making Your SAS Output, Results, Reports, Charts and Spreadsheets More Meaningful with Color |
Kirk Paul Lafler |
|
20 |
| MWSUG |
2018 |
Visual Storytelling - The Art of Communicating Information with Graphics |
Kirk Paul Lafler |
|
16 |
| WUSS |
2018 |
Analyzing international assessments: An ensemble and model comparison approach |
Chong Ho Yu,
Hyun Seo Lee,
Siyan Gan,
Emily Lara |
source |
13 |
| WUSS |
2018 |
CDISC in Phase I/II Studies: Approaches to adopting standards for CSR deliverables |
Emily Woolley,
Amber Randall |
source |
9 |
| WUSS |
2018 |
Data-Driven Data Analysis |
Jack N. Shoemaker |
source |
10 |
| WUSS |
2018 |
How sensitive is your analysis? A case study on addressing it at ADaM level. |
Bhargav Koduru,
Balavenkata Pitchuka |
source |
7 |
| WUSS |
2018 |
Innovation and Your Career in a Rapidly Changing World of Job Titles: How Different is Data Scientist from What I Do? |
Richelle Serrano |
source |
5 |
| WUSS |
2018 |
Machine Learning - Why we should know it and how it works |
Kevin Lee |
source |
8 |
| WUSS |
2018 |
Making Your SAS Results, Reports, Tables, Charts and Spreadsheets More Meaningful with Color |
Kirk Paul Lafler |
source |
20 |
| WUSS |
2018 |
The Hidden Job Market: Tips and Techniques to Advance Your SAS Career |
Molly Hall |
source |
15 |
| WUSS |
2018 |
Time Series Analysis of Hate Speech in Social Media |
David J. Corliss |
source |
8 |
| WUSS |
2018 |
When the Mean Isn't Enough: Methods for Assessing Individual Differences using SAS |
Melissa McTernan |
source |
8 |
| PHUSE US |
2018 |
Adverse Event Analysis - One step forward! |
Anuja Rasal |
source
presentation source |
11 |
| PHUSE US |
2018 |
Assuring Data Integrity and Data Quality in Sponsor Submissions |
Paul Schuette |
source
presentation source |
5 |
| PHUSE US |
2018 |
Building Dashboards for Real-time Insights into Clinical Data |
Bhavin Busa,
Siddartha Kondapally |
source |
6 |
| PHUSE US |
2018 |
Cross-study Analysis of SDTM Data Using R |
Greg Jones,
Todd Cornelius |
source
presentation source |
6 |
| PHUSE US |
2018 |
Data Science Applications and Scenarios |
Edwin Ponraj Thangarajan,
Giri Balasubramanian |
source
presentation source |
13 |
| PHUSE US |
2018 |
Don't Sweat It! Consider Taking the Risk Out of your Outsourced Deliverables |
Jennifer True,
Nancy Haeusser |
source
presentation source |
4 |
| PHUSE US |
2018 |
FDA Experience with Emerging Genomics Technologies [presentation] |
Weida Tong |
source |
16 |
| PHUSE US |
2018 |
Mine the Gap: How the Role of Data Scientist Fills a Need in the Pharmaceutical Industry |
Michael S Rimler,
Jorine Putter |
source
presentation source |
8 |
| PHUSE US |
2018 |
PHUSE Working Groups - Now & Nex |
Chris Price,
Scott A. Bahlavooni |
source
poster source |
7 |
| PHUSE US |
2018 |
Post-Marketing Surveillance and the FAERS Big Data Paradox |
Aditya Gadiko |
source
poster source |
3 |
| PHUSE US |
2018 |
PowerDataExplorer - Data Exploration in an All-In-One Dynamic Report Using SAS & EXCEL |
Harry Chen,
Lisa Lyons |
source
presentation source |
8 |
| PHUSE US |
2018 |
R or Python: A Programmer's Response |
Jiangtang Hu |
source |
3 |
| PHUSE US |
2018 |
SAS Programming is Done by Human Beings |
Ray Mckinnis |
source
presentation source |
4 |
| PHUSE US |
2018 |
The First and Last Words of ADaM |
Susan J. Kenny |
source |
4 |
| PharmaSUG |
2018 |
A Method for Independent Program Validation utilising SAS, R and Python |
Aik Hoe Seah |
source |
13 |
| PharmaSUG |
2018 |
A Simple Method for Integrating Analysis Result Metadata into Existing Define.xml 2.0 |
Jeff Xia |
source |
9 |
| PharmaSUG |
2018 |
A Statistician's Guide to Leadership and Success |
Heather Murphy |
source |
5 |
| PharmaSUG |
2018 |
ADaM Integration for Summary of Clinical Safety: The 'Unique Patient' Paradox |
Aakar Shah,
Tracy Sherman |
source |
12 |
| PharmaSUG |
2018 |
An Efficient Tool for Clinical Data Check |
Chao Su |
source |
8 |
| PharmaSUG |
2018 |
BEACH: an open platform for building interactive and automatic analysis powered by R/Shiny |
Danni Yu,
Michael Man |
source |
19 |
| PharmaSUG |
2018 |
Exploring use of R for Clinical trials |
Kalpesh Prajapati,
Parvee Kumar |
source |
7 |
| PharmaSUG |
2018 |
How PK and PD analyses drive dataset designs |
David Radtke,
Brian A. Moser |
source |
7 |
| PharmaSUG |
2018 |
How to Be a Great (Stats or Programming) Manager: Advice from an Underling |
Mary Grovesteen |
source |
6 |
| PharmaSUG |
2018 |
Implementation of ADaM Basic Data Structure on Genetic Variation Data for Pharmacogenomics Studies |
Linghui Zhang |
source |
10 |
| PharmaSUG |
2018 |
Implementation of Data Cut Off in Analysis of Clinical Trials |
Mei Dey |
source |
15 |
| PharmaSUG |
2018 |
Machine Learning - Why we should know and How it works |
Kevin Lee |
source |
8 |
| PharmaSUG |
2018 |
Mining Mass Fragments using SAS and Python for Metabolite Identification of Antibody-Drug Conjugates |
Hao Sun,
Kristen Cardinal |
source |
5 |
| PharmaSUG |
2018 |
Preventing premature unblinding in PK/PD related studies |
Debbie Sisco,
Alice Zong |
source |
11 |
| PharmaSUG |
2018 |
Processing and Cleaning Streaming Data in SAS |
Mehmet Kocak |
source |
10 |
| PharmaSUG |
2018 |
Review programs used for submission and their input to the define-XML 2.0 |
Ari Siggaard Knoph,
Morten Hasselstrm Jensen,
Bo Sølgaard Andersen |
source |
11 |
| PharmaSUG |
2018 |
Sense and Censorability: Learn censoring techniques with ADTTE for your survival |
Shilpakala Vasudevan |
source |
12 |
| PharmaSUG |
2018 |
Some Common Programming Errors and Possible Solutions That Could Impact a Successful NDA/BLA |
Amos Shu |
source |
5 |
| PharmaSUG |
2018 |
Statistical Programming: Revolution, Evolution, or Status Quo? |
Jeffrey M. Abolafia,
Frank C. DiIorio |
source |
9 |
| PharmaSUG |
2018 |
Telling Stories with Jupyter Notebook |
Kevin Lee |
source |
14 |
| PharmaSUG |
2018 |
The Changing Clinical Data Analytics Landscape - Visualization & Beyond |
Siddartha Kondapally,
Kishore Pothuri,
Bhavin Busa |
source |
6 |
| PharmaSUG |
2018 |
To Error is Human: An Overview of Human Errors in SAS Programming and How to Mitigate Them |
Nagadip Rao |
source |
9 |
| PharmaSUG |
2018 |
Traceability: Some Thoughts and Examples for ADaM Needs |
Richann J. Watson,
Kent Letourneau,
Wayne (Weizhen) Zhong,
Sandra Minjoe |
source |
18 |
| PharmaSUG |
2018 |
Using Agile Analytics for Data Discovery in the Pharma Industry |
Bob Matsey |
source |
4 |
| SGF |
2018 |
Accelerate your End-to-End Enterprise Decisions with SAS Viya |
David R. Duling,
Steve Sparano |
source |
12 |
| SGF |
2018 |
Adopt A Pet (Elephant?): Are You Enjoying Your Apache Hadoop Investment? |
Rex Pruitt |
source |
16 |
| SGF |
2018 |
An Ingenuity Journey to Set ROI and Benefits Tracking |
John Jarrett |
source |
3 |
| SGF |
2018 |
Analytics Like a Pro: The Differences between My Fantasy Team and Production Analytics in Sports [presentation] |
Timothy Trussell |
source |
21 |
| SGF |
2018 |
Are New Modeling Techniques Worth It? |
Tom Zougas |
source |
8 |
| SGF |
2018 |
Creating a Successful Data Science Program: A Joint Academic and Industry Perspective |
Krzysztof Dzieciolowski |
source |
6 |
| SGF |
2018 |
Data Science and SAS : A Data Science Perspecitve [presentation] |
Richard W. La Valley |
source |
32 |
| SGF |
2018 |
Demystifying Buzzwords: Using Data Science and Machine Learning on Unsupervised Big Data |
Ben Murphy |
source |
10 |
| SGF |
2018 |
Docker Toolkit for Data Scientists: How to Start Doing Data Science in Minutes! |
Donna De Capite |
source |
29 |
| SGF |
2018 |
Enterprise, Prepare for Analysis! Using SAS Data Management to Prepare Data for Analysis |
Bob Janka |
source |
17 |
| SGF |
2018 |
Improved Campaigning at Africa's Largest Pay TV Service Provider with SAS Marketing Optimization |
Jean De Villiers |
source |
16 |
| SGF |
2018 |
Indication of Irregularities in the Accumulation of Public Sector Jobs in the State of Ceará (Brazil) |
Jose Silva,
Raimundo Filho |
source |
11 |
| SGF |
2018 |
Interpreting Black-Box Machine Learning Models Using Partial Dependence and Individual Conditional Expectation Plots |
Ray Wright |
source |
19 |
| SGF |
2018 |
SAS Analytics Pro Running in a Docker Container in a Cloud Environment [presentation] |
Brian Bream,
Frank Daniels |
source |
1 |
| SGF |
2018 |
Text Analytics Lessons Learned: When MAUDE Doesn't Talk to You |
Grace Heyne Lybrand,
Reid Baughman,
Ingrid Lundberg,
Michael Swanson |
source |
9 |
| SGF |
2018 |
The Anatomy of Clinical Trials Data: A Beginner's Guide |
Venky Chakravarthy |
source |
14 |
| SGF |
2018 |
Time Series Analysis of Hate Speech in Social Media |
David J. Corliss |
source |
12 |
| SGF |
2018 |
Using SAS to Teach Credit Risk: From Undergraduate Studies to Professional Education [presentation] |
Cristian Bravo |
source |
25 |
| SESUG |
2017 |
An Introduction to Visit Window Challenges and Solutions |
Mai Ngo |
source |
6 |
| SESUG |
2017 |
Can A SAS Programmer Stay Cool |
Jiangtang Hu |
source |
6 |
| SESUG |
2017 |
Data Analysis and Storytelling - Communicating Analytical Results with Clarity, Precision and Efficiency |
Kirk Paul Lafler |
source |
10 |
| SESUG |
2017 |
I Spy PII: Detect, Protect, and Monitor Personal Data with SAS Data Management |
Cecily Hoffritz |
source |
33 |
| SESUG |
2017 |
Job Upward Mobility: Getting Better When You're Already Good |
Molly Meade Hall |
source |
11 |
| SESUG |
2017 |
Missing Data and Complex Sample Surveys Using SAS: The Impact of Listwise Deletion vs. Multiple Imputation Methods on Point and Interval Estimates when Data are MCAR, MAR, and MNAR |
Listwise Deletion |
source |
26 |
| SESUG |
2017 |
Streamlining ADaM Dataset Specifications |
Hunter Vega |
source |
6 |
| SESUG |
2017 |
You as a Brand: Tips for Managing Your Data Career |
Patricia S. Aanderud |
source |
5 |
| SCSUG |
2017 |
A Study on H1B - VISA Petitions 2011-2016 |
Shubham Panat |
source |
12 |
| SCSUG |
2017 |
Data Analysis and Storytelling - Communicating Analytical Results with Clarity, Precision and Efficiency |
Kirk Paul Lafler |
source |
10 |
| PHUSE EU |
2017 |
A Joke Stereotypes and Communication |
Sarah Berenbrinck |
source
presentation source |
4 |
| PHUSE EU |
2017 |
A User Interface to Your SAS Programs |
Hailemichael Worku |
source
presentation source |
10 |
| PHUSE EU |
2017 |
ADaM Mapping - KeyConsiderations forMetadata Driven Realization |
Elenea Gathe |
source |
12 |
| PHUSE EU |
2017 |
An FDA Submission Experience Using the CDISC Standards |
Angelo Tinazzi,
Cédric Marchand |
source
presentation source |
15 |
| PHUSE EU |
2017 |
Analysis Results Metadata 1.0 for Define-XML 2.0 - Benefits to Statistical Analysis |
Lionel Debecq |
source
presentation source |
12 |
| PHUSE EU |
2017 |
Approach to EMA Policy 0070 - From Data Science Perspective |
Jorine Putter |
source
presentation source |
6 |
| PHUSE EU |
2017 |
Assessing New CFDA Requirements on Data Integrity Using Risk-Based Monitoring and Enrollment Patterns |
Wenjun Bao,
Richard C. Zink,
Geoffrey A. Mann |
source
presentation source |
13 |
| PHUSE EU |
2017 |
Career Development Through Job Rotation: Cases and Lessons Learned |
Simon Wang |
source
presentation source |
2 |
| PHUSE EU |
2017 |
Dipping our Fingers into the World of Data Representation - A Visual Journey Using Encapsia Clinica |
Minola Ilica |
source
presentation source |
4 |
| PHUSE EU |
2017 |
EMA Policy 0070: Data Utility in Anonymized Clinical Study Reports (CSRs) |
Jean-Marc Ferran,
Sarah Nevitt |
source |
23 |
| PHUSE EU |
2017 |
Enabling Data Driven Culture via Technology |
Chandi Kodthiwada |
source
presentation source |
3 |
| PHUSE EU |
2017 |
Growing Up with SAS: It Gets Real |
Yevhen Los,
Dmytro Hasan |
source
presentation source |
6 |
| PHUSE EU |
2017 |
Health Technology Assessment PRO Least Squares Mean Difference Programming Techniques Using SAS |
Yirong Cao,
Siory Traoré |
source
presentation source |
11 |
| PHUSE EU |
2017 |
Implementation of CDISC ADaM and Pharmacodynamics |
Françoise Frérart,
Joanna Magielse |
source
presentation source |
5 |
| PHUSE EU |
2017 |
Statistical End User Tool Development |
Mickael Borne |
source
presentation source |
15 |
| PHUSE EU |
2017 |
The Model Statistician Insights into Model Selection Techniques in Clinical Trials |
Peter Williams |
source
presentation source |
6 |
| PHUSE EU |
2017 |
Topology-based Clinical Data Mining: Identifying Hidden Patterns in Clinical Datasets |
Sergey Glushakov |
source
presentation source |
18 |
| PHUSE EU |
2017 |
Visualizing Multiple Endpoints: Extending the Use of Forest Plots in Clinical Trials |
James R. Johnson,
Mark Jaros |
source
presentation source |
10 |
| MWSUG |
2017 |
AIR Binder 2.0: A Dynamic Visualization, Data Analysis and Reporting SAS Application for Preclinical and Clinical ADME Assays, Pharmacokinetics, Metabolite Profiling and Identification |
Hao Sun,
Kristen Cardinal,
Richard Voorman |
|
26 |
| MWSUG |
2017 |
Unconventional Statistical Models with the NLMIXED Procedure |
Robin High |
|
14 |
| WUSS |
2017 |
A SAS Format Catalog for ICD-9/ICD-10 Diagnoses and Procedures: Data Research Example and Custom Reporting Example |
Robert Springborn |
source |
37 |
| WUSS |
2017 |
Job Upward Mobility: Getting Better When You're Already Good |
Molly Hall |
source |
11 |
| WUSS |
2017 |
Making a Difference With SAS |
Humberto Cisneros,
Carrin Huff |
source |
15 |
| WUSS |
2017 |
Standardized Approaches for Analyzing Quality Improvement Interventions in Healthcare Settings |
Polina Kukhareva |
source |
20 |
| WUSS |
2017 |
Which Paint Brush Shall I Choose -- Mapping Out Your Visualization Plan for Clinical Studies |
Chen Shi |
source |
5 |
| PharmaSUG CN |
2017 |
Effective Statistical Programming Preparation and Support for CFDA Self-Inspections and Onsite Inspections |
Peng Wan |
|
5 |
| PharmaSUG |
2017 |
ADaM Grouping: Groups, Categories, and Criteria. Which Way Should I Go? |
Jack Shostak |
source |
12 |
| PharmaSUG |
2017 |
AIR Binder: An Automatic Reporting and Data Analysis SAS Application for Cytochrome P450 Inhibition Assay to Investigate DDI |
Hao Sun,
Kristen Cardinal,
Carole Kirby,
Richard Voorman |
source |
8 |
| PharmaSUG |
2017 |
Challenge for Dramatic Streamlining of TLFs Creation Process with SAS and Java |
Yohei Takanami,
Fumihiro Yamasaki |
source |
8 |
| PharmaSUG |
2017 |
Creating Define-XML version 2 including Analysis Results Metadata with the SAS Clinical Standards Toolkit |
Lex Jansen |
source |
31 |
| PharmaSUG |
2017 |
Documenting Traceability for the FDA: Clarifying the Legacy Data Conversion Plan & Introducing the Study Data Traceability Guide |
David C. Izard,
Kristin Kelly,
Jane Lozano |
source |
9 |
| PharmaSUG |
2017 |
Good Programming Practices at Every Level |
Maria Dalton |
source |
6 |
| PharmaSUG |
2017 |
Here Comes The Smart Mock Table: A Novel Way of Creating Clinical Summary Tables Without Any Table Programming (No Kidding!) |
Joseph W. Hinson |
source |
19 |
| PharmaSUG |
2017 |
Implementing Patient Report Outcome data in clinical trials analysis |
Qi Wang |
source |
7 |
| PharmaSUG |
2017 |
In-Licensing from a Programming Perspective |
Asif Karbhari |
source |
5 |
| PharmaSUG |
2017 |
Innovation and Regulatory Review What is JumpStart? |
Alan Shapiro |
source |
24 |
| PharmaSUG |
2017 |
Mentoring and Oversight of Programmers across Cultures and Time Zones |
Chad W. Melson |
source |
7 |
| PharmaSUG |
2017 |
Multinomial Logistic Regression Models With Sas Proc Surveylogistic |
Marina Komaroff |
source |
7 |
| PharmaSUG |
2017 |
Preparing Analysis Data Model (ADaM) Data Sets and Related Files for FDA Submission |
Sandra Minjoe |
source |
12 |
| PharmaSUG |
2017 |
SAS and R Playing Nice Together |
David Edwards,
Bella Feng,
Brian Schultheiss |
source |
3 |
| PharmaSUG |
2017 |
Standardized, Customized or Both? Defining and Implementing (MedDRA) Queries in ADaM Data Sets |
Richann J. Watson,
Karl Miller |
source |
7 |
| PharmaSUG |
2017 |
Topology-based Clinical Data Mining for Discovery of Hidden Patterns in Multidimensional Data |
Sergey Glushakov,
Iryna Kotenko,
Andrey Rekalo |
source |
20 |
| PharmaSUG |
2017 |
Translating Statistics into Knowledge by Examples Using SAS Graphic Procedures |
Tao Shu,
Jianfei Jiang |
source |
11 |
| PharmaSUG |
2017 |
Work with me here-(or there or anywhere): Practical Cloud Collaboration with JMP Clinical for Clinical Trial Data Reviews |
Kelci J. Miclaus,
Drew Foglia |
source |
14 |
| PharmaSUG |
2017 |
Writing Efficient Queries in SAS Using PROC SQL with Teradata |
Mina Chen |
source |
5 |
| SGF |
2017 |
A Hadoop Journey along the SAS Road |
Sumit Sukhwani,
Krutharth Peravalli,
Amit Gautam |
source |
8 |
| SGF |
2017 |
Analyzing the Effectiveness of COPD Drugs Through Statistical Tests and Sentiment Analysis |
Indra Kiran Chowdavarapu,
Dursun Delen,
Vivek Manikandan Damodaran |
source |
23 |
| SGF |
2017 |
Auto Telematics: Deviations Drive Success |
Kelsey Osterloo,
Deovrat Kakde |
source |
12 |
| SGF |
2017 |
Convergence of Big Data, the Cloud, and Analytics: A Docker Toolbox for the Data Scientist |
Donna De Capite |
source |
11 |
| SGF |
2017 |
Creating the Perfect BI Report: Where to Begin |
Lisa Eckler |
source |
17 |
| SGF |
2017 |
Data Science Rex: How Data Science Is Evolving (or Facing Extinction) across the Academic Landscape |
Jennifer Priestley |
source |
6 |
| SGF |
2017 |
Developing Your Own SAS Studio Custom Tasks for Advanced Analytics |
Elliot Inman,
Olivia Wright |
source |
20 |
| SGF |
2017 |
Exploration of Information Technology-Related Barriers Affecting Rural Primary Care Clinics |
Ipe Simon Paramel,
Ankita Srivastava,
Onkar Jadhav,
Jennifer Briggs,
Georgina Ankrah |
source |
11 |
| SGF |
2017 |
I Spy PII: Detect, Protect, and Monitor Personally Identifiable Information with SAS Federation Server |
Cecily Hoffritz |
source |
33 |
| SGF |
2017 |
Impact of Outbound SMS notifications on Inbound Interactive Voice Response Call Volume |
Sumit Sukhwani,
Krutharth Peravalli,
Dmitriy Khots |
source |
7 |
| SGF |
2017 |
Interactive Modeling in SAS Visual Analytics |
Donald R. Chapman,
Jonathan Wexler |
source |
16 |
| SGF |
2017 |
Investigating Big-Data Crime Scenes |
Theresa H. Ngo |
source |
10 |
| SGF |
2017 |
Know Your Tools Before You Use |
Justin Jia |
source |
16 |
| SGF |
2017 |
Meta-Analysis of Human Trafficking in the United States |
David J. Corliss,
Heather Hill |
source |
8 |
| SGF |
2017 |
Preparing Analysis Data Model (ADaM) Data Sets and Related Files for FDA Submission with SAS |
Sandra Minjoe,
John K. Troxell |
source |
12 |
| SGF |
2017 |
Quality Control Programming: A Lost Art? |
Amber Randall,
Bill Coar |
source |
15 |
| SGF |
2017 |
Retracing My SAS Global Forum 2016 Steps: Visualizing iPhone Health App Step Data With a (What Else?) Step Plot |
Ted Conway |
source
pdf |
8 |
| SGF |
2017 |
Revolutionizing Statistical Computing in SAS with the Jupyter Notebook |
Hunter Glanz |
source |
9 |
| SGF |
2017 |
Statistical Volunteering With SAS - Experiences and Opportunities |
David J. Corliss |
source |
8 |
| SGF |
2017 |
The Effects of Socioeconomic, Demographic Variables on US Mortality Using SAS Visual Analytics |
Catherine Loveless-Schmitt |
source
pdf |
22 |
| SGF |
2017 |
The Well-Equipped Student: Using SAS University Edition and E-Learning to Gain SAS Skills |
Randy Mullis,
Allison Mahaffey |
source |
19 |
| SESUG |
2016 |
A Short Introduction to Longitudinal and Repeated Measures Data Analyses |
Leanne Goldstein |
source |
19 |
| SESUG |
2016 |
Creating Viable SAS Data Sets From Survey Monkey Transport Files |
John R. Gerlach |
source |
11 |
| SESUG |
2016 |
Make the Jump from Business User to Data Analyst in SAS Visual Analytics |
Ryan Kumpfmilller |
source |
13 |
| SESUG |
2016 |
Missing Data and Complex Sample Surveys Using SAS: The Impact of Listwise Deletion vs. Multiple Imputation on Point and Interval Estimates when Data are MCAR and MAR |
Anh P. Kellermann,
DeAnn Trevathan,
Jeffrey D. Kromrey |
source |
12 |
| SESUG |
2016 |
SDTM What? ADaM Who? A Programmer's Introduction to CDISC |
Venita DePuy |
source |
9 |
| SESUG |
2016 |
Success Takes Balance: Don't Fall Over with Your SAS Visual Analytics Implementation |
Craig Willis,
Ryan Kumpfmiller,
Patricia S. Aanderud |
source |
7 |
| PHUSE EU |
2016 |
Adventures in Data Science |
Kieran Martin |
source |
9 |
| PHUSE EU |
2016 |
Analysis Datasets for Baseline Characteristics and Exposure Time for Multi-stage Clinical Trials |
Kimberly Umans,
Katherine Riester |
source
presentation source |
5 |
| PHUSE EU |
2016 |
Constructing Interoperable Study Documents From A Semantic Technology-based Repository |
Colin de Klerk |
source
presentation source |
12 |
| PHUSE EU |
2016 |
encapsia - Providing Real-time, Interactive Visualisations of Clinical Data [presentation] |
Jon Carter |
source |
9 |
| PHUSE EU |
2016 |
How a Metadata Repository Enables Dynamism and Automation in SDTM-like SAS Dataset Generation |
Judith Goud,
Akana Shetty |
source
presentation source |
7 |
| PHUSE EU |
2016 |
How Macro Design and Program Structure Impact GPP (Good Programming Practice) in TFL Coding |
Galyna Repetatska |
source
presentation source |
8 |
| PHUSE EU |
2016 |
How to Review a CRF - A Statistical Programmer's Perspective |
Elsa Lozachmeur |
source
presentation source |
7 |
| PHUSE EU |
2016 |
Integrating the New EMA Requirements on Public Disclosure in the Study Conduct [presentation] |
Jean-Marc Ferran |
source |
20 |
| PHUSE EU |
2016 |
On the Fast Lane to a Successful Submission - A Lead Programmer's Guide to Efficient, High-quality Submission Programming Deliverables |
Michael Reich,
Hannes Engberg Raeder |
source
presentation source |
9 |
| PHUSE EU |
2016 |
Planning for Data Reporting Processes for Submission: Key Considerations |
Parag Shiralkar |
source
presentation source |
2 |
| PHUSE EU |
2016 |
Standard Methods for Analysis and Reporting of VAS or NRS Derived Pain Relief Response Scores |
James R. Johnson |
source
presentation source |
14 |
| PHUSE EU |
2016 |
The Hardships of Finding your Way in Biometrics |
Evi Creebsburg |
source |
4 |
| PHUSE EU |
2016 |
Upstream with Your Statistician and a Data Visualisation Paddle |
Nick Cowans |
source
presentation source |
6 |
| MWSUG |
2016 |
Mentoring and Oversight of Programmers across Cultures and Time Zones |
Chad W. Melson |
|
6 |
| MWSUG |
2016 |
Read html files and create standard tables for BISR at KUMC |
Chuanwu Zhang,
John Keighley,
Byron J. Gajewski |
|
7 |
| MWSUG |
2016 |
Statistical Volunteering With SAS - Experiences and Opportunities |
David J. Corliss |
|
8 |
| MWSUG |
2016 |
The Practice of Credit Risk Modeling for Alternative Lending |
Keith Shields,
Bruce S. Lund |
|
8 |
| MWSUG |
2016 |
The State of Human Trafficking in the Cincinnati Metropolitan Area - a Statistical Case Study |
David J. Corliss,
Heather M. Hill |
|
8 |
| WUSS |
2016 |
Creating Dynamic Documents with SAS in the Jupyter Notebook to Reinforce Soft Skills |
Hunter Glanz |
source |
6 |
| WUSS |
2016 |
Creating Viable SAS Data Sets From Survey Monkey Transport Files |
John R. Gerlach,
Independent Contractor |
source |
11 |
| WUSS |
2016 |
Reproducible Data Science Using SAS in a Jupyter Notebook |
Hunter Glanz |
source |
6 |
| WUSS |
2016 |
Short Introduction to Reliability Engineering and PROC RELIABILITY to Non-Engineers |
Danny Rithy |
source |
7 |
| PharmaSUG |
2016 |
"It is a standard, so it is simple, right?": Misconceptions and Organizational Challenges of Implementing CDISC at a CRO |
Susan H.M. Boquist,
Adam J. Sicard |
source |
5 |
| PharmaSUG |
2016 |
Career Path for SAS Profession in Pharmaceutical Industry |
James Meiliang Yue |
source |
2 |
| PharmaSUG |
2016 |
Creating Define-XML version 2 including Analysis Results Metadata with the SAS Clinical Standards Toolkit |
Lex Jansen |
source |
29 |
| PharmaSUG |
2016 |
Don-t Agonize, Organize: Maximizing efficiency and effectiveness of SAS Programming in Clinical Trials projects, by using Project Management Organizing Methodologies |
Shefalica Chand |
source |
8 |
| PharmaSUG |
2016 |
Handling Interim and Incomplete Data in a Clinical Trials Setting |
Paul Stutzman |
source |
13 |
| PharmaSUG |
2016 |
Mixed Effects Models |
Yan Wang |
source |
7 |
| PharmaSUG |
2016 |
Preparing the Data to Ensure Correct Calculation of Relative Risk |
Ravi Kankipati,
Abhilash Chimbirithy |
source |
13 |
| PharmaSUG |
2016 |
SAS and R - stop choosing, start combining and get benefits! |
Diana Bulaienko |
source |
7 |
| PharmaSUG |
2016 |
Summarizing Adverse Events of Interest - Onset, Duration, and Resolution |
John Saida Shaik,
Avani Kaja |
source |
6 |
| PharmaSUG |
2016 |
What makes a "Statistical Programmer" different from a "Programmer" |
Arun Raj Vidhyadharan,
Sunil Mohan Jairath |
source |
12 |
| PharmaSUG |
2016 |
Working with Composite Endpoints: Constructing Analysis Data |
Pushpa Saranadasa |
source |
7 |
| SGF |
2016 |
A Pseudo-Interactive Approach to Teaching SAS Programming |
Hunter Glanz |
source
zip |
6 |
| SGF |
2016 |
A Short Introduction to Longitudinal and Repeated Measures Data Analyses |
Leanne Goldstein |
source |
19 |
| SGF |
2016 |
Analyzing Non-Normal Binomial and Categorical Response Variables under Varying Data Conditions |
Niloofar Ramezani |
source |
16 |
| SGF |
2016 |
Assessing Undergraduate and Postgraduate Hard and Soft Skills in Analytics and Data Science Courses |
Richard Self |
source |
8 |
| SGF |
2016 |
Bayesian Inference for Gaussian Semiparametric Multilevel Models |
Jason Bentley,
Cathy Yuen Yi Lee |
source
zip |
19 |
| SGF |
2016 |
Can You Stop the Guesswork in Your Marketing Budget Allocation? Marketing Mixed Modeling Using SAS Can Help! |
Delali Agbenyegah |
source |
7 |
| SGF |
2016 |
Careers in Biotatistics and Clinical SAS Programming: An Overview for the Uninitiated |
Justina M. Flavin |
source |
5 |
| SGF |
2016 |
Enhanced Segmentation Using SAS Visual Analytics and SAS Visual Statistics |
Darius S. Baer,
Suneel Grover |
source |
19 |
| SGF |
2016 |
Event Stream Processing for Enterprise Data Exploitation |
Tho H. Nguyen,
Fiona McNeill |
source |
7 |
| SGF |
2016 |
Everyone CAN be a Data Scientist: Using SAS Studio to Create a Custom Task for SAS In-Memory Statistics |
Stephen Ludlow |
source |
20 |
| SGF |
2016 |
Is It Time for a PhD in Data Science? [presentation] |
Jennifer Priestley |
source |
15 |
| SGF |
2016 |
Making it Happen: A Novel Way to Save Taxpayer Dollars by Implementing an In-House SAS Data Analytics and Research Center |
Vivek Sethunatesan |
source |
11 |
| SGF |
2016 |
Mass-Scale, Automated Machine Learning and Model Deployment Using SAS Factory Miner and SAS Decision Manager |
Jonathan Wexler,
Steve Sparano |
source |
19 |
| SGF |
2016 |
Medicare Fraud Analytics Using Cluster Analysis: How PROC FASTCLUS Can Refine the Identification of Peer Comparison Groups |
Paulo Macedo |
source
zip |
9 |
| SGF |
2016 |
Missing Values: They Are NOT Nothing |
Justin Jia,
Shan Shan Lin |
source |
19 |
| SGF |
2016 |
Multiple-Group Multiple Imputation: An Empirical Comparison of Parameter Recovery in the Presence of Missing Data using SAS |
Patricia Rodríguez de Gil,
Jeffrey D. Kromrey |
source |
15 |
| SGF |
2016 |
Prescriptive Analytics - Providing the Instruction to Do What's Right |
Tho H. Nguyen,
Fiona McNeill |
source
presentation |
11 |
| SGF |
2016 |
PROC IMSTAT Boosts Knowledge Discovery in Big-Database (KDBD) in a Pharmaceutical Company |
Yoshitake Kitanishi,
Ryo Kiguchi,
Akio Tsuji,
Hideaki Watanabe |
source |
7 |
| SGF |
2016 |
Product Purchase Sequence Analyses by Using a Horizontal Data Sorting Technique |
Justin Jia,
Shan Shan Lin |
source
presentation |
11 |
| SGF |
2016 |
SAS Global Forum [presentation] |
Bob Matsey |
source |
37 |
| SGF |
2016 |
SAS Visual Statistics 8.1: The New Self-Service, Easy Analytics Experience |
Xiangxiang Meng,
Donald R. Chapman,
Cheryl LeSaint |
source |
11 |
| SGF |
2016 |
Statistical Comparisons of Disease Prevalence Rates Using the Bootstrap Procedure |
Matthew Dutton,
Charlotte Baker |
source |
6 |
| SGF |
2016 |
Streaming Decisions: How SAS Puts Streaming Data to Work |
Fiona McNeill,
David R. Duling,
Steve Sparano |
source
zip |
15 |
| SGF |
2016 |
Using SAS to Conduct Multivariate Statistical Analysis in Educational Research: Exploratory Factor Analysis and Confirmatory Factor Analysis |
Jun Xu,
Steven L. Holtzman,
Kevin Petway,
Lili Yao |
source |
13 |
| MWSUG |
2015 |
Can You Stop the Guesswork in Your Marketing Budget Allocation? Marketing Mixed Modeling Using SAS Can Help! |
Delali Agbenyegah |
|
7 |
| PHUSE EU |
2015 |
A Modularised Approach to the Development of a Data Science Tool |
Guiseppe Di Monaco |
source
presentation source |
10 |
| PHUSE EU |
2015 |
A Simple and Novel Approach for the Assessment of Clinical Pharmacokinetics (Fast-track PK Analysis) [presentation] |
Ramanatha Saralaya,
Nand Kishore Rawat |
source |
12 |
| PHUSE EU |
2015 |
A StAR is Born: AstraZeneca/Quintiles Partnering for Success |
Alison Dobson,
Alex Brink |
source
presentation source |
6 |
| PHUSE EU |
2015 |
Analysing the Role of a Lead Programmer |
Ester Schoeman |
source
presentation source |
9 |
| PHUSE EU |
2015 |
Automated generation of program templates with metadata based specification documents for integrated analysis |
Thomas Wollseifen |
source
presentation source |
11 |
| PHUSE EU |
2015 |
CDISC Standards and the Semantic Web |
David Iberson-Hurst |
source
presentation source |
9 |
| PHUSE EU |
2015 |
Data Governance - Keeping Control through a Well-defined Changes Request Process |
Gavin Winpenny |
source
presentation source |
9 |
| PHUSE EU |
2015 |
Data Scientist - What It Is (Not) |
Michaela Jahn |
source
presentation source |
4 |
| PHUSE EU |
2015 |
Ensuring Data Quality in Outsourced Studies - The Role of the Data Scientist |
Sarah Malbon,
Vikki Horton |
source
presentation source |
8 |
| PHUSE EU |
2015 |
Facing Your Fear of the Unknown - Handling Missing Data |
Amanda Reilly |
source
presentation source |
7 |
| PHUSE EU |
2015 |
Flexible Solutions for Insight and Data-driven Innovation |
Catharina Dahblo |
source
presentation source |
6 |
| PHUSE EU |
2015 |
From Data Management to Statistical Programming: A Real-Life Change |
Benjamin Lerbour |
source
presentation source |
5 |
| PHUSE EU |
2015 |
Generating Multiple Parameter Reports into Single Reports Using %Do Loop and CALL SYMPUTX |
Krishna Gohil |
source
presentation source |
5 |
| PHUSE EU |
2015 |
Graphics in R - A Shiny Way to Program |
Carolyn Nixon |
source
presentation source |
12 |
| PHUSE EU |
2015 |
Introduction to GPP with Hints and Tips to Make them Second Nature |
Alexandra Marquat,
Shafi Chowdhury |
source
presentation source |
7 |
| PHUSE EU |
2015 |
Statistical Analysis Reporting Tool (StART), From Concept to Table Production |
David M. Hartman |
source
presentation source |
11 |
| PHUSE EU |
2015 |
Study Anonymisation: From Request to Delivery |
Kelly Mewes,
Sai Jandhyala |
source
presentation source |
11 |
| PHUSE EU |
2015 |
The Rewarding (and Rocky) Road from SAS Applications Programmer to SAS Software Developer |
Jeffrey M. Abolafia,
Carrie Dundas-Lucca |
source
presentation source |
8 |
| PHUSE EU |
2015 |
The Vision of Clinical Data Science - Where will we be in 2025? [presentation] |
Sam Warden,
Chris Price |
source |
17 |
| PHUSE EU |
2015 |
Unleashing the Analyst: Establishing a Department of Dynamic Real-world Data Science (RWD-S) Analysts who are able to Partner, Influence and Drive the Generation of Real-world Evidence |
Ryan Copping,
Robert Walls |
source
presentation source |
28 |
| PHUSE EU |
2015 |
Working as a Data Scientist with Real-world Clinical Data |
Berber Snoeijer |
source
presentation source |
2 |
| SESUG |
2015 |
Coder ' |
s Corner |
source |
10 |
| SESUG |
2015 |
How to be a Data Scientist Using SAS |
Charles D. Kincaid,
Experis Business |
source |
13 |
| SESUG |
2015 |
Reporting of treatment emergent adverse events based on pooled data Analysis or Country Specific Submissions: A case study |
Sheetal Shiralkar |
source |
8 |
| SESUG |
2015 |
Tips and Tricks for Introductory Workshops in SAS for Health Professionals |
Jason Brinkley |
source |
4 |
| WUSS |
2015 |
A Pseudo-Interactive Approach to Teaching SAS Programming |
Hunter Glanz |
source |
4 |
| WUSS |
2015 |
A Short Introduction to Longitudinal and Repeated Measures Data Analyses |
Leanne Goldstein |
source |
19 |
| WUSS |
2015 |
Chi-Square and T-Tests Using SAS: Performance and Interpretation |
Jennifer L. Waller,
Maribeth H. Johnson |
source |
12 |
| WUSS |
2015 |
Leveraging APIs in SAS to Create Interactive Visualizations |
Rebecca Ottesen |
source |
13 |
| WUSS |
2015 |
No Regrets: Hiring for the Long Term in Statistical Programming |
Chris Moriak,
Graham Wilson,
Elizabeth Meeson |
source |
7 |
| WUSS |
2015 |
SAPs are for saps: A guide to the ins and outs of SAPs in iterative, observational, or publication-oriented research |
Michelle Turner,
Lawrence Rasouliyan |
source |
4 |
| WUSS |
2015 |
Yes, PROC FREQ does that! |
AnnMaria De Mars |
source |
15 |
| PharmaSUG CN |
2015 |
SAS End-to-End solutions in Clinical Trial |
Emma Liu |
|
17 |
| PharmaSUG CN |
2015 |
Why Statistical Analysis Plan (SAP) should be comprehensive. |
Riddhi Merchant,
Ranjith Prayankotveettil |
|
6 |
| PharmaSUG |
2015 |
Creating output datasets using SQL (Structured Query Language) only |
Andrii Stakhniv |
source |
10 |
| PharmaSUG |
2015 |
Forest Plots: Old Growth versus GMO (Genetically Modified Organism) |
Scott Horton |
source |
12 |
| PharmaSUG |
2015 |
Improving Data Quality - Missing Data Can Be Your Friend! |
Julie Chen |
source |
12 |
| PharmaSUG |
2015 |
Japanese submission/approval processes from programming perspective |
Ryan Hara |
source |
7 |
| PharmaSUG |
2015 |
Lessons Learned from the QC Process in Outsourcing Model |
Faye Yeh |
source |
5 |
| PharmaSUG |
2015 |
Managing the Evolution of SAS Programming |
Carey G. Smoak |
source |
4 |
| PharmaSUG |
2015 |
MMRM: Macro for Selecting Best Covariance Structure with the Method of Interest |
Linga Reddy Baddam,
Sudarshan Reddy Shabadu,
Chunxue Shi |
source |
7 |
| PharmaSUG |
2015 |
No Regrets: Hiring for the Long Term in Statistical Programming |
Chris Moriak,
Graham Wilson,
Elizabeth Meeson |
source |
7 |
| PharmaSUG |
2015 |
Schoveing Series 1: Motivating and Inspiring Statistical Programmers in the Biopharmaceutical Industry |
Priscilla Gathoni |
source |
10 |
| PharmaSUG |
2015 |
Statistical Analyses Across Overlapping Time Intervals Based on Person-Years |
John Reilly,
John R. Gerlach |
source |
10 |
| PharmaSUG |
2015 |
Team-work and Forensic Programming: Essential Foundations of Indestructible Projects |
Brian P. Fairfield-Carter |
source |
14 |
| PharmaSUG |
2015 |
The Disposition Table: Make it Easy |
Endri Endri,
Benedikt Trenggono |
source |
10 |
| PharmaSUG |
2015 |
The Implementation of Display Auto-Generation with Analysis Results Metadata Driven Method |
Chengxin Li |
source |
11 |
| PharmaSUG |
2015 |
Variable-Width Plot - SAS GTL Implementation |
Songtao Jiang |
source |
6 |
| SGF |
2015 |
A New Method of Using Polytomous Independent Variables with Many Levels for the Binary Outcome of Big Data Analysis |
John Gao,
Jesse Harriott,
Lisa Pimentel |
source |
7 |
| SGF |
2015 |
Analysis of Survey Data Using the SAS SURVEY Procedures: A Primer |
Patricia A. Berglund |
source |
19 |
| SGF |
2015 |
Chi-Square and T-Tests Using SAS: Performance and Interpretation |
Jennifer L. Waller,
Maribeth H. Johnson |
source |
12 |
| SGF |
2015 |
Educating Future Business Leaders in the Era of Big Data |
Tonya E. Balan |
source |
8 |
| SGF |
2015 |
Getting Your Hands on Reproducible Graphs |
Rebecca Ottesen,
Leanne Goldstein |
source |
19 |
| SGF |
2015 |
Meter Data Analytics--Enabling Actionable Decisions to Derive Business Value from Smart Meter Data |
Tom Anderson,
Jennifer Whaley |
source |
11 |
| SGF |
2015 |
SAS Does Data Science: How to Succeed in a Data Science Competition |
Patrick Hall |
source
zip |
11 |
| SGF |
2015 |
Statistical Analysis of Publicly Released Survey Data with SAS/STAT Software SURVEY Procedures |
Donna Brogan |
source |
20 |
| SGF |
2015 |
Structuring your SAS Applications for Long-Term Survival: Reproducible Methods in Base SAS Programming |
Paul Thomas |
source
zip |
13 |
| SGF |
2015 |
Visualizing Clinical Trial Data: Small Data, Big Insights |
Michael Drutar,
Elliot Inman |
source |
18 |
| SGF |
2015 |
Yes, SAS Can Do! Manage External Files with SAS Programming |
Justin Jia,
Amanda Lin |
source |
14 |
| SESUG |
2014 |
SAS Enterprise Guide for Institutional Research and Other Data Scientists |
Claudia W. McCann |
source |
20 |
| SESUG |
2014 |
SDTM What? ADaM Who? A Programmer's Introduction to CDISC |
Venita DePuy |
source |
9 |
| SESUG |
2014 |
Tools for Managing and Measuring the Value of Big Data Projects |
Robert W. Phelps |
source |
6 |
| SESUG |
2014 |
Using Regression Model to Predict Cyclic Resistance Ratio at South Carolina Coastal Plain (SCCP) |
Emad Gheibi,
Sarah L. Gassman,
Abbas S. Tavakoli |
source |
10 |
| PHUSE EU |
2014 |
ADaM Conversions: The Good, The Bad and The Ugly |
Carla Santillán,
Jessica Minuke |
source
presentation source |
11 |
| PHUSE EU |
2014 |
Concept for a Clinical Trial Reporting System |
Daniil Shliakhov |
source
presentation source |
2 |
| PHUSE EU |
2014 |
Data Challenges in Adaptive Trials |
Claudio Garutti |
source
presentation source |
5 |
| PHUSE EU |
2014 |
Do You Like What You See? - Understanding Data in Magnetic Resonance Imaging Studies |
Oliver Wirtz |
source
presentation source |
7 |
| PHUSE EU |
2014 |
Every Study is Special! - Governing Data Standards |
Chris Price,
Elizabeth Nicol |
source
presentation source |
12 |
| PHUSE EU |
2014 |
From Gene Expression to Expression Cartography, Grade Correspondence Analysis Application in Class Comparison Studies |
Edyta Winciorek |
source
presentation source |
6 |
| PHUSE EU |
2014 |
From ODM to SDTM: An End-to-End Approach Applied to Phase I Clinical Trials |
Alexandre Mathis |
source
presentation source |
5 |
| PHUSE EU |
2014 |
Implementation of CDISC ADaM in the Pharmacokinetics Department |
Joanna Magielse,
Tineke Callant |
source
presentation source |
6 |
| PHUSE EU |
2014 |
Japanese Submission/Approval from Programming Perspective |
Ryan Hara |
source
presentation source |
5 |
| PHUSE EU |
2014 |
Lessons Learned by Comparing "using SAS" as and Epidemiological Researcher and "using SAS" as a Statistical Programmer |
Joris Derks |
source
presentation source |
6 |
| PHUSE EU |
2014 |
Managing the Change - Evolving Statistical Programmers to Clinical Data Scientists |
Sascha Ahrweiler |
source
presentation source |
10 |
| PHUSE EU |
2014 |
Programming and Statistics in the Academics Environment [presentation] |
Arne Ring |
source |
21 |
| PHUSE EU |
2014 |
SAS in Clinical Trial - A Relook at Project Management, Tools and Software Engineering |
Sameera Nandigama |
source
presentation source |
12 |
| PHUSE EU |
2014 |
Spotfire for Clinical and Translational Medicine |
Gerard Conway |
source |
3 |
| PHUSE EU |
2014 |
Standards Driven Innovation [presentation] |
Frederik Malfait |
source |
36 |
| PHUSE EU |
2014 |
Unuttered Questions of Statistical Programmers |
Aparajita Dey |
source
presentation source |
10 |
| MWSUG |
2014 |
Use of Social Media Data to Predict Retail Sales Performance |
Li Zhang |
|
13 |
| PharmaSUG CN |
2014 |
Design and Construct Efficacy Analysis Datasets in Later Phase Oncology Study |
Huadan Li,
Changhong Shi |
|
9 |
| PharmaSUG CN |
2014 |
Submission of Pharmacokinetics (PK) Data in a CDISC Compliant Format |
Yu Zhu |
|
9 |
| PharmaSUG CN |
2014 |
Using SAS SG Procedures to Create and Enhance Figures in Pharmaceutical Industry |
Shuo Chi,
Huashan Huo |
|
12 |
| WUSS |
2014 |
A Hitchhiker's guide for performance assessment & benchmarking SAS applications |
Viraj R Kumbhakarna |
source |
16 |
| WUSS |
2014 |
Big Data in a Small Trial: Visual and Statistical Analyses in an N-of-1 Clinical Trial |
Marie Boman-Davis |
source |
6 |
| WUSS |
2014 |
Careers in Biostatistics and Clinical SAS Programming: An Overview for the Uninitiated |
Justina M. Flavin |
source |
5 |
| WUSS |
2014 |
Design of Experiments (DOE) Using JMP [presentation] |
Charles E. Shipp |
|
16 |
| WUSS |
2014 |
Quick Analysis and Visualization of Excluded and Missing Data |
Polina Kukhareva |
source |
9 |
| WUSS |
2014 |
Reanalysis of Ecological Data from the 1989 China Study Using SAS Enterprise Guide |
Thomas E. Billings |
source |
17 |
| WUSS |
2014 |
When Software Development is Your Means Not Your End: Abstracting Agile Methodologies for End-User Development and Analytic Application |
Troy Martin Hughes |
source |
17 |
| PharmaSUG |
2014 |
%IC_LOGISTIC: A SAS Macro to Produce Sorted Information Criteria (AIC/BIC) List for PROC LOGISTIC for Model Selection |
Qinlei Huang,
Liang Zhu |
source |
12 |
| PharmaSUG |
2014 |
Automatic Access Control via SAS: More Efficient and Smart |
Yuichi Koretaka,
Masakazu Fujiwara,
Yuki Yoshida,
Yoshitake Kitanishi |
source |
10 |
| PharmaSUG |
2014 |
Automation of ADAM Dataset Creation with a Retrospective, Prospective and Pragmatic Process |
Karin LaPann,
Terek J. Peterson |
source |
6 |
| PharmaSUG |
2014 |
Careers in Biostatistics and Clinical SAS Programming: An Overview for the Uninitiated |
Justina M. Flavin |
source |
5 |
| PharmaSUG |
2014 |
Challenges of Processing Questionnaire Data from Collection to SDTM to ADaM and Solutions Using SAS |
Karin LaPann,
Terek J. Peterson |
source |
20 |
| PharmaSUG |
2014 |
Clinical Study Report Review: Statistician's Approach |
Amita Dalvi |
source |
6 |
| PharmaSUG |
2014 |
D is for Dynamic, putting Dynamic back into CDISC (A simple macro utilizing PROC SQL which auto-formats continuous variables for lab tables) |
Steven C. Black |
source |
9 |
| PharmaSUG |
2014 |
Defining Non-Inferiority Margins for Skin Adhesion Studies |
Marina Komaroff,
Sailaja Bhaskar |
source |
12 |
| PharmaSUG |
2014 |
Effective Use of Metadata in Analysis Reporting |
Jeffrey M. Abolafia |
source |
9 |
| PharmaSUG |
2014 |
Evaluating the benefits of JMP for SAS programmers |
Xiaopeng Li,
Chun Feng,
Nancy Wang |
source |
9 |
| PharmaSUG |
2014 |
From "Just Shells" to a Detailed Specification Document for Tables, Listings and Figures |
Supriya Dalvi |
source |
13 |
| PharmaSUG |
2014 |
Handling with missing data in clinical trials for time-to-event variables |
Giulia Tonini,
Simona Scartoni,
Angela Capriati |
source |
9 |
| PharmaSUG |
2014 |
Healthcare Data Manipulation and Analytics Using SAS |
Lumin Shen,
Jane Lu |
source |
11 |
| PharmaSUG |
2014 |
Methodology for Non-Randomized Clinical Trials: Propensity Score Analysis |
Dan Conroy |
source |
5 |
| SGF |
2014 |
An Overview of Machine Learning with SAS Enterprise Miner |
Patrick Hall,
Jared Dean,
Ilknur Kaynar Kabul,
Jorge Silva |
source
zip |
24 |
| SGF |
2014 |
Automatic Detection of Section Membership for SAS Conference Paper Abstract Submissions: A Case Study |
Goutam Chakraborty,
Murali Krishna Pagolu |
source |
13 |
| SGF |
2014 |
Challenges of Processing Questionnaire Data from Collection to SDTM to ADaM and Solutions Using SAS |
Karin LaPann,
Terek J. Peterson |
source |
19 |
| SGF |
2014 |
CMS Core Measures, the Affordable Care Act, and SAS Visual Analytics |
Joe Whitehurst,
Diane Hatcher |
source |
16 |
| SGF |
2014 |
Healthcare Services Data Distribution, Transformation, and Model Fitting |
Dawit Mulugeta,
Jason Greenfield,
Tison Bolen,
Lisa Conley |
source |
22 |
| SGF |
2014 |
How to be a Data Scientist Using SAS |
Chuck Kincaid |
source |
13 |
| SGF |
2014 |
Integrated Big Data: Hadoop + DBMS + Discovery for SAS High-Performance Analytics |
John Cunningham |
source |
9 |
| SGF |
2014 |
Near Time, Real Time&Big; Time |
Michael Ralston |
source |
10 |
| SGF |
2014 |
Star Wars and the Art of Data Science: An Analytical Approach to Understanding Large Amounts of Unstructured Data |
Adam Maness,
Mary Osborne |
source |
28 |
| SGF |
2014 |
The Desert and the Dunes: Finding Oases and Avoiding Mirages with the SAS Visual Analytics Explorer |
Nascif Abousalh-Neto |
source |
15 |
| SGF |
2014 |
Turn Your SAS Macros into Microsoft Excel Functions with the SAS Integrated Object Model and ADO |
Chris Brooks |
source |
17 |
| SGF |
2014 |
Using Arrays for Epidemic Modeling in SAS |
Carl Grafe |
source |
7 |
| WUSS |
2013 |
From Database to your Desktop: How to almost completely automate reports in SAS, with the power of Proc SQL |
Kirtiraj Mohanty,
Trinh Nguyen |
source |
8 |
| WUSS |
2013 |
How to be a Data Scientist Using SAS |
Chuck Kincaid |
source |
13 |
| WUSS |
2013 |
Telling Stories with Your Data - Graphs, Tables and Basic, Basic Statistics with SAS Enterprise Guide |
AnnMaria De Mars |
source |
19 |
| SESUG |
2013 |
A Hitchhiker's guide for performance assessment & benchmarking SAS applications |
Viraj R Kumbhakarna |
source |
16 |
| SESUG |
2013 |
Chi-Square and T-Tests Using SAS: Performance and Interpretation |
Jennifer L. Waller,
Maribeth H. Johnson |
source |
12 |
| PHUSE EU |
2013 |
CARE to CRaM |
Greg Fuller |
source
presentation source |
16 |
| PHUSE EU |
2013 |
eBESTreports - The Fastest Way to Conclusions [presentation] |
Tuomas Kemppainen,
Juha Hyssala |
source |
25 |
| PHUSE EU |
2013 |
Interpreting CDISC ADaM IG Through Users Interpretation |
Angelo Tinazzi |
source
presentation source |
12 |
| PHUSE EU |
2013 |
Mission Possible: Your Assignment is to Validate Output for a Study |
Susan Fehrer Coulson |
source
presentation source |
7 |
| PHUSE EU |
2013 |
Oncology Endpoints: An Unexpected Journey |
Waseem Jugon,
Mijanur Rahman |
source |
12 |
| PHUSE EU |
2013 |
One Vision, Many Interpretations? |
Todd Case |
source
presentation source |
3 |
| PHUSE EU |
2013 |
Orphan Indication Therapies: Programming for a Patient Population without Options [presentation] |
Todd Case |
source |
24 |
| PHUSE EU |
2013 |
Pain of Your Back(up) or Efficient Resourcing of Back-up Solutions for Programming Leads |
Adam Amborski |
source
presentation source |
5 |
| PHUSE EU |
2013 |
Posch-Bauer Seamless Test with SAS |
Antonio Nieto,
Javier Gómez |
source
presentation source |
4 |
| PHUSE EU |
2013 |
Standard Protocols Using Guided Navigation [presentation] |
Michaela Jahn |
source |
15 |
| PHUSE EU |
2013 |
Standards for the Management of Clinical Trial Data, Why are they Needed, What is Needed? |
Isabelle Abousahl |
source
presentation source |
11 |
| PHUSE EU |
2013 |
The Missing Link: Results Level Metadata |
Jeffrey M. Abolafia |
source
presentation source |
9 |
| PHUSE EU |
2013 |
Using PROC GENMOD to Analyses Ratio to Placebo in Change of Dactylitis |
Imgard Hollweck |
source
presentation source |
9 |
| MWSUG |
2013 |
SAS PROC REPORT: How It Helps Improving College Student Retention Rate |
Harjanto Djunaidi,
Monica Djunaidi |
|
14 |
| NESUG |
2013 |
How to be a Data Scientist Using SAS |
Chuck Kincaid |
|
13 |
| NESUG |
2013 |
Managing Statistical Programmers across the Great Divide: An Odyssey of CRO's, Big and Small Pharma and Biotech, and in NJ, CA and Boston |
Todd Case |
|
3 |
| NESUG |
2013 |
Nearly Instant SAS Programming |
Michael L. Davis |
|
12 |
| NESUG |
2013 |
The ADaM Solutions to Non-endpoints Analyses |
Chengxin Li |
|
12 |
| PharmaSUG |
2013 |
Deployment of SAS Programming Contract Staff: Pathway to Sinkhole or Best Strategy for Programming Division? |
Parag Shiralkar |
source |
5 |
| PharmaSUG |
2013 |
Flags for Facilitating Statistical Analysis Using CDISC Analysis Data Model |
Chun Feng,
Xiaopeng Li,
Nancy Wang |
source |
6 |
| PharmaSUG |
2013 |
From Standards that Cost To Standards that Save: Cost Effective Standards Implementation |
Jeffrey M. Abolafia,
Frank C. DiIorio |
source |
9 |
| PharmaSUG |
2013 |
Introduction to the CDISC Standards |
Sandra Minjoe |
source |
10 |
| PharmaSUG |
2013 |
Is Your Data Set Really Validated: Beware of "Blind-Fold" Validation |
Nehan Mohan,
Gayatri Karkera |
source |
4 |
| PharmaSUG |
2013 |
Just Press the Button: Generation of SAS Code to Create Analysis Datasets directly from an SAP - Can it be Done? |
Endri Endri,
Rowland Hale |
source |
8 |
| PharmaSUG |
2013 |
Map Metadata - Going Beyond the Obvious/Connecting the Dots |
Gregory C. Steffens,
Praveen Garg |
source |
8 |
| PharmaSUG |
2013 |
Mission Possible: Your Assignment is to Validate Output for a Study |
Susan Fehrer Coulson,
Kevin R. Coulson |
source |
7 |
| PharmaSUG |
2013 |
More Power to SAS - Embedding Other Programming Languages in SAS Through SAS/IML Studio |
Max Cherny |
source |
10 |
| PharmaSUG |
2013 |
Practice of SMQs for Adverse Events in Analysis of Safety Data and Pharmacovigilance |
Gary Chen,
David Shen |
source |
11 |
| PharmaSUG |
2013 |
SAS Programmer to Clinical SAS Programmer |
Gayatri Karkera,
Nehan Mohan |
source |
7 |
| PharmaSUG |
2013 |
Standardizing the Standards: A Road Map for Establishing, Implementing and Unifying Standards in Your Organization |
Amy Caison,
Jhelum Naik,
Tammy Jackson |
source |
9 |
| PharmaSUG |
2013 |
Time to Event Analysis in the Pharmaceutical and Medical Device Industries |
Helen M. Chmiel,
Evan L. Ritzema |
source |
8 |
| PharmaSUG |
2013 |
Transition from "hands-on" statistical programmer to leader of a team of role based statistical programmers. Tools and tips to help you succeed. |
Rodrigo Juarez y Ruiz |
source |
9 |
| SGF |
2013 |
Bringing Churn Modeling Straight to the Source: SAS and Teradata In-Database Model Development |
Jonathan Wexler,
Karl Krycha |
source |
9 |
| SGF |
2013 |
Chi-Square and T-Tests Using SAS: Performance and Interpretation |
Jennifer L. Waller,
Maribeth H. Johnson |
source |
12 |
| SGF |
2013 |
Employee Wellness Programming Using SAS Enterprise Guide |
Sandra Brooks,
Tina Hembree,
Yehia H. Khalil |
source |
7 |
| SGF |
2013 |
For All the Hats You Wear: SAS Enterprise Guide Has Got You Covered |
Chris Hemedinger |
source |
8 |
| SGF |
2013 |
Here Is How We Do It: Teaching SAS at Community Colleges |
Meili Xu |
source
pdf |
6 |
| SGF |
2013 |
Horizontal Data Sorting and Insightful Reporting: A Useful SAS Technique |
Amanda Lin,
Justin Jia |
source |
14 |
| SGF |
2013 |
Implementing CDISC, SDTM, and ADaM in a SAS Environment |
Pankaj Bhardwaj |
source
pdf |
4 |
| SGF |
2013 |
Models for Ordinal Response Data |
Robin High |
source |
16 |
| SGF |
2013 |
Statistical Analyses Using SAS Enterprise Guide |
Scott P. Leslie |
source |
11 |
| SGF |
2013 |
The Forest and the Trees: See It All with SAS Visual Analytics Explorer |
Nascif Abousalh-Neto |
source |
14 |
| SGF |
2013 |
Time Is Precious, So Are Your Models: SAS Provides Solutions to Streamline Deployment |
Jonathan Wexler,
Wayne Thompson |
source |
17 |
| NESUG |
2012 |
Developing an Analytics Center of Excellence (Or The Care and Feeding of Magical Creatures) |
Chuck Kincaid |
|
11 |
| NESUG |
2012 |
Quality Assurance: Best Practices in Clinical SAS Programming |
Parag Shiralkar |
|
8 |
| NESUG |
2012 |
Running SAS on the Grid |
Margaret A. Crevar |
|
10 |
| PHUSE EU |
2012 |
A Peak at PK - An Introduction to Pharmacokinetics |
Hannah Twittchet,
Paul Grimsey |
source
presentation source |
9 |
| PHUSE EU |
2012 |
A Supplement to the SAS Survival Guide - Nonparametric Regression |
Karl-Ernst Siegler |
source
presentation source |
8 |
| PHUSE EU |
2012 |
A Tool to Catalogue Statistical Outputs Developed for Submission by Linking Two in-house systems |
Katja Diezel |
source
poster source |
6 |
| PHUSE EU |
2012 |
ADaM Or SDTM? A Comparision of Pooling Strategies for Integrated Analyses in the Age of CDISC |
Joerg Guettner,
Alexandru Cuza |
source
presentation source |
7 |
| PHUSE EU |
2012 |
Considerations for CSR Output Production from ADaM Datasets |
Andrew Noller |
source
presentation source |
1 |
| PHUSE EU |
2012 |
Cost Effective Standards Implementation: A New Paradigm for the Drug Development Life Cycle |
Jeff Abolafio,
Frank C. DiIorio |
source
presentation source |
9 |
| PHUSE EU |
2012 |
Medical Data Review and Exploratory Data Analysis using Data Visualization |
Vinod Kerai |
source
poster source |
6 |
| PHUSE EU |
2012 |
One Approach to a Metadata and Data Standards Repository |
Bill J. Gibson |
source
poster source |
4 |
| PHUSE EU |
2012 |
Programming By Rules |
Magnus Mengelbier |
source
poster source |
4 |
| PHUSE EU |
2012 |
Risk-Benefit Analysis for Oncology Clinical Trials |
Lovemore Gakava,
Waseem Jugon |
source
poster source |
8 |
| PHUSE EU |
2012 |
Training Statistical Programmers on SAP Review Skills |
Sascha Ahrweiler |
source
presentation source |
7 |
| SESUG |
2012 |
A Randomization Test SAS/IML Program for Making Treatment Effects Inferences for Extensions and Variations of ABAB Single-Case Experimental Designs |
Patricia Rodríguez de Gil,
John M. Ferron |
source |
8 |
| SESUG |
2012 |
A SAS Programming Framework for Data Extraction Using Perl Regular Expression: The First Wave |
Jiangtang Hu |
source |
10 |
| SESUG |
2012 |
Compare MIXED and GLMMIX to Analyze Breast Cancer Longitudinal Study |
Abbas S. Tavakoli |
source |
5 |
| SESUG |
2012 |
Getting to the Good Part of Data Analysis: Data Access, Manipulation, and Customization Using JMP |
Audrey Ventura |
source |
19 |
| SESUG |
2012 |
How to Perform and Interpret Chi-Square and T-Tests |
Jennifer L. Waller |
source |
14 |
| SESUG |
2012 |
Integration of Scientific Writing into an Applied Biostatistics and SAS Programming Course for Pharmaceutical Sciences Graduate Students |
Daniel L. Hertz,
Daniel J. Crona,
Jasmine Talameh,
Scott J. Brantley,
Luke Roode,
Katherine N. Theken,
J. Heyward Hull |
source |
7 |
| SESUG |
2012 |
Running SAS on the Grid |
Margaret A. Crevar |
source |
10 |
| SESUG |
2012 |
The Elephant in the Room: Hadoop & SAS Integration Greenplum, SAS & Hadoop |
Chris Stephens |
|
23 |
| MWSUG |
2012 |
Developing an Analytics Center of Excellence (Or The Care and Feeding of Magical Creatures) |
Charles D. Kincaid |
|
11 |
| MWSUG |
2012 |
Getting the Code Right the First Time |
Michael C. Frick |
|
11 |
| MWSUG |
2012 |
Getting to the Good Part of Data Analysis: Data Access, Manipulation, and Customization Using JMP |
Audrey Ventura |
|
19 |
| MWSUG |
2012 |
Models for Ordinal Response Data |
Robin High |
|
11 |
| MWSUG |
2012 |
Preparing Your Computer for SAS Grid |
Margaret A. Crevar,
Tony Brown |
|
10 |
| WUSS |
2012 |
Developing an Analytics Center of Excellence (Or The Care and Feeding of Magical Creatures) |
Chuck Kincaid |
source |
11 |
| WUSS |
2012 |
Exploratory and Descriptive Data Analysis for Site-Level Outcomes |
Amanda Stevenson |
source |
7 |
| WUSS |
2012 |
SAS Rule-Based Codebook Generation for Exploratory Data Analysis |
Ross Bettinger |
source |
8 |
| PharmaSUG CN |
2012 |
A SAS Macro Application to Create Mock Tables in Statistical Analysis Plans for Phase I Clinical Studies |
Yao Huang |
|
7 |
| PharmaSUG |
2012 |
"Analysis-ready" - Considerations, Implementations, and Real World Applications |
Ellen (Zihui) Lin,
Beiying Ding |
source |
6 |
| PharmaSUG |
2012 |
A Hitchhiker's guide for performance assessment & benchmarking SAS applications |
Viraj R Kumbhakarna,
Anurag Katare |
source |
16 |
| PharmaSUG |
2012 |
A Practice to Create Executable SAS Programs for Regulatory Agency Reviewers |
Hongyu Liu,
Lynn Anderson,
James R. O'Hearn,
Kexi Chen |
source |
6 |
| PharmaSUG |
2012 |
Application of Meta-Analysis in Clinical Trials |
Marina Komaroff |
source |
7 |
| PharmaSUG |
2012 |
CDISC ADaM Application: Does All One-Record-per-Subject Data Belong in ADSL? |
Sandra Minjoe |
source |
10 |
| PharmaSUG |
2012 |
Common Misunderstandings about ADaM Implementation |
Nate Freimark,
Susan J. Kenny,
Jack Shostak,
John K. Troxell |
source |
10 |
| PharmaSUG |
2012 |
Creating the Time to Event ADaM Dataset: The Nuts and Bolts |
Nancy Brucken,
Paul K. Slagle |
source |
7 |
| PharmaSUG |
2012 |
Giving Data a Voice: Partnering with Medical Writing for Best Reporting Practices |
Katherine Troyer,
Brit Minor |
source |
8 |
| PharmaSUG |
2012 |
Making a List, Checking it Twice: Efficient Production and Verification of Tables and Figures Using SAS |
Linda Collins,
Elizabeth Li |
source |
17 |
| PharmaSUG |
2012 |
Managing Programmers across the Great Divide: An Odyssey in managing CRO-s, in Big and Small Pharma, Biotech and Pharma and in NJ, CA and Boston |
Todd Case |
source |
3 |
| PharmaSUG |
2012 |
Quick Data Definitions Using SQL, REPORT and PRINT Procedures |
Bradford J. Danner |
source |
5 |
| PharmaSUG |
2012 |
Streamlining Regulatory Submission with CDISC/ADaM Standards for Non-standard Pharmacokinetic/Pharmacodynamic Analysis Datasets |
Xiaopeng Li,
Katrina E. Canonizado,
Chun Feng,
Nancy Wang |
source |
6 |
| SGF |
2012 |
A Hitchhiker's Guide for Performance Assessment and Benchmarking SAS Applications |
Viraj R Kumbhakarna,
Anurag Katare |
source |
17 |
| SGF |
2012 |
Defining the Development Process and Governance of Implementing ADaM within an Organization |
Chris Decker |
source |
11 |
| SGF |
2012 |
Enhanced Data Analysis Using SAS ODS Graphics and Statistical Graphics |
Patricia A. Berglund |
source |
20 |
| SGF |
2012 |
Getting to the Good Part of Data Analysis: Data Access, Manipulation, and Customization Using JMP |
Audrey Ventura |
source |
19 |
| SGF |
2012 |
Guidelines for Preparing Your Computer Systems for SAS |
Margaret A. Crevar,
Tony Brown |
source |
10 |
| SGF |
2012 |
How to Perform and Interpret Chi-Square and T-Tests |
Jennifer L. Waller |
source |
20 |
| SGF |
2012 |
Knowledge (of Your Missing Data) Is Power: Handling Missing Values in Your SAS Data Set |
Theresa Schwartz,
Rachel Zeig-Owens |
source |
8 |
| SGF |
2012 |
Let Oil and Gas Talk to You: Predicting Production Performance |
Keith R. Holdaway |
source |
12 |
| SGF |
2012 |
SAS Social Media or How I Learned to Love the Blog |
Christopher Battiston |
source |
3 |
| SGF |
2012 |
Seamless Reporting Automation through the Integration of JMP, SAS, and VBA |
Rachel Poulsen,
Raghunathan Chakravarthy |
source |
10 |
| SGF |
2012 |
The Emergence of Patterns in SAS Usage and Infrastructure |
Chuck Kincaid,
Mike R Vanderlinden |
source |
15 |
| SGF |
2012 |
Using DDE and VBA Techniques to Import Data from Microsoft Word Tables in Programming Specification Files into SAS |
Mei Li,
Zemin Zeng |
source |
9 |
| SGF |
2012 |
Using SAS PROC MIXED to Fit Health Policy-Based Hierarchical Models |
Lori L. Miller,
Fred Wilds |
source |
7 |
| SCSUG |
2011 |
Advice to Health Services Researchers: Be Cautious Using the "Where" Statement in SAS Programs for Nationally Representative Complex Survey Data |
Hemalkumar Mehta |
source |
10 |
| SCSUG |
2011 |
Statistical comparison of relative proportions of bacterial genetic sequences |
Jose F Garcia-Mazcorro |
source |
19 |
| SESUG |
2011 |
Eyes on the Road: A Methodology for Analyzing Complex Eye-Tracking Data |
Eye Tracking |
source |
11 |
| SESUG |
2011 |
Graphing a Progression of Time Series Plots |
Nathaniel Derby |
source |
11 |
| SESUG |
2011 |
Missing_Items: A SAS Macro for Missing Data Imputation in Summative Response Scales |
Patricia Rodríguez de Gil,
Jeffrey D. Kromrey |
source |
13 |
| SESUG |
2011 |
Proc MIXED - Right Options to get Right Output |
Shilpa C. Edupganti,
Sheetal Nisal |
source |
9 |
| WUSS |
2011 |
Graphing a Progression of Time Series Plots with ODS Graphics |
Nathaniel Derby |
source |
11 |
| WUSS |
2011 |
Helping Students Become Effective Industry Statisticians: Supplementing Science with Data Savvy |
Aleksandra Stein |
source |
5 |
| WUSS |
2011 |
SAS Procedure Proc Mixed to Assess the Effects of School Health Policy Requirements on Change in Student Health Outcomes |
Lori Miller |
source |
9 |
| WUSS |
2011 |
Statistical Analyses Using SAS Enterprise Guide |
R. Scott Leslie |
source |
11 |
| WUSS |
2011 |
This is how we do it: teaching SAS in the Cal Poly Statistics Department |
Rebecca Ottesen |
source |
12 |
| WUSS |
2011 |
Turbocharging Your Microsoft Office Environment with version 4.3 of the SAS Add-In for Microsoft Office |
Kevin Bickford |
source |
21 |
| PHUSE EU |
2011 |
Creating ADaM Friendly Analysis Data from SDTM Using Meta Data |
Erik Brun,
Rico Schiller |
source
presentation source |
6 |
| PHUSE EU |
2011 |
Defining the Governance and Process of Implementing ADaM across an Organization |
Chris Decker |
source
presentation source |
11 |
| PHUSE EU |
2011 |
Rebuilding define.pdf by reading Word and XFDF files |
David J. Garbutt |
source
poster source |
23 |
| PHUSE EU |
2011 |
SDTM Domain QS: Challenges and Pitfalls - an Interpretation Guide to the Implementation Guide |
Knut Mueller |
source
presentation source |
6 |
| PHUSE EU |
2011 |
State of the union: what does the future hold for statistical programming in Europe [presentation] |
Leo Valmas |
source |
28 |
| PHUSE EU |
2011 |
Training Statistical Programmers on SAP Review Skills |
Sascha Ahrweiler |
source
presentation source |
7 |
| PHUSE EU |
2011 |
Using R to Validate Results of Other Programming Environments |
Nikhil Abhyankar,
Vidyagouri Prayag |
source
presentation source |
8 |
| MWSUG |
2011 |
A Hitchhiker's guide for performance assessment & benchmarking SAS applications |
Viraj R Kumbhakarna,
Anurag Katare |
|
16 |
| MWSUG |
2011 |
Bootstrap power analysis using SAS |
Douglas Thompson,
Nort Holschuh,
Bruce Barton,
Ann Albertson |
|
8 |
| MWSUG |
2011 |
Graphing a Progression of Time Series Plots with ODS Graphics |
Nathaniel Derby,
Laura Vo,
Perry Watts |
|
11 |
| MWSUG |
2011 |
The Emergence of Patterns in SAS Usage and Infrastructure |
Chuck Kincaid,
Mike R Vanderlinden |
|
13 |
| MWSUG |
2011 |
Using a Double DOW Loop to Compute Progression Free Survival |
Matthew Nizol |
|
9 |
| NESUG |
2011 |
A Missing Guide for a Comprehensive Kaplan-Meier Plot |
Jiannan Hu |
|
7 |
| NESUG |
2011 |
Proc Mixed - Right Options to Get the Right Output |
Shilpa C. Edupganti,
Sheetal Nisal |
|
10 |
| NESUG |
2011 |
Waterfall Charts: Play the Mario with Your Data |
Niraj J. Pandya,
Sapan Raval |
|
7 |
| PharmaSUG |
2011 |
Brave New World: How to Adapt to the CDISC Statistical Computing Environment |
Jeffrey M. Abolafia,
Frank C. DiIorio |
source |
11 |
| PharmaSUG |
2011 |
Challenges in Implementing ADaM datasets: Balancing the Analysis-Ready and Traceability Concepts |
Pushpa Saranadasa |
source |
7 |
| PharmaSUG |
2011 |
Clinical Trials Versus Health Outcomes Research: SAS/STAT Versus SAS Enterprise Miner |
Patricia B. Cerrito |
source |
15 |
| PharmaSUG |
2011 |
Helping Students Become Effective Industry Statisticians: Supplementing Science with Data Savvy |
Aleksandra Stein,
Steven R. Kirby |
source |
5 |
| PharmaSUG |
2011 |
Implementation of Pattern-Mixture Models Using Standard SAS/STAT Procedures |
Bohdana Ratitch,
Michael O'Kelly |
source |
10 |
| PharmaSUG |
2011 |
Keeping Patients on Schedule, The Art of Visit Windows and Cycle Slotting |
Paul K. Slagle |
source |
4 |
| PharmaSUG |
2011 |
Making a List, Checking it Twice (Part 1): Techniques for Specifying and Validating Analysis Datasets |
Elizabeth Li,
Linda Collins |
source |
8 |
| PharmaSUG |
2011 |
Statistical Analysis of Adverse Events in Randomized Clinical Trials Using SAS |
Dongsun Cao,
Xiaomin He |
source |
12 |
| PharmaSUG |
2011 |
Success As a Pharmaceutical Statistical Programmer |
Sandra Minjoe,
Mario Widel |
source |
7 |
| PharmaSUG |
2011 |
Using SAS for Modeling and Simulation in Drug Development - A Review and Assessment of Some Available Tools |
Melvin S. Munsaka,
Michael Carniello |
source |
10 |
| SGF |
2011 |
An Introduction to Survival Analysis Using Complex Sample Survey Data |
Patricia A. Berglund |
source |
20 |
| SGF |
2011 |
Applied Revolutionary BI |
Charles D. Kincaid |
source |
16 |
| SGF |
2011 |
Making SAS Enterprise Guide Easier to Use |
Tom Kari |
source |
9 |
| SGF |
2011 |
Making Use of Incomplete Observations in the Analysis of Structural Equation Models: The CALIS Procedures Full Information Maximum Likelihood Method in SAS/STAT 9.3 |
Yiu-Fai Yung,
Wei Zhang |
source |
20 |
| SGF |
2011 |
To Hash or Not To Hash! That Is the Question!! When it Comes to SQL!!! |
Mustaq Ahmad |
source |
12 |
| SGF |
2011 |
Turbocharging Your Microsoft Office Environment with SAS Add-In for Microsoft Office 4.3 |
Anand V. Chitale |
source |
21 |
| SGF |
2011 |
Using Microsoft Access 2007 Description of Field Names in Tables as Variable Labels in SAS Data Sets |
Maria S. Melguizo,
Jerry Stalnaker,
Christopher J. Swearingen |
source |
5 |
| SGF |
2011 |
Visualize Your Cloud Data Using the Graph Template Language |
Krishnan Raghupathi |
source |
12 |
| SGF |
2011 |
Writing SAS Programs with SAS and Microsoft Excel: Generate Batch SAS Programs Based on SAP Specifications |
Laiju Zhang |
source |
7 |
| NESUG |
2010 |
Functional Data Analysis on SAS system |
Le Yin |
|
9 |
| NESUG |
2010 |
Process Monitoring and Control of Semiconductor Production Tools Using JMP |
Peter Frankwicz,
Don Scipione,
Steven Coleman,
John Devlin |
|
10 |
| NESUG |
2010 |
Using SAS/AF to Create an Interactive Interface for Entering and Analyzing Data |
William 'Gui' Zupko II |
|
22 |
| NESUG |
2010 |
Using Simple Code to Enter Complex Data from Base SAS to SAS/AF |
William 'Gui' Zupko II |
|
16 |
| WUSS |
2010 |
101 Applications of Multivariate Statistical Procedures: PRINCOMP, CLUSTER, DISCRIM in SAS 9.2 |
Keh-Dong Shiang |
source |
22 |
| WUSS |
2010 |
A SAS/IntrNet Based Application to Enhance the Efficiency and Productivity of a Company |
Bing Hu |
source |
10 |
| WUSS |
2010 |
Answering Your Research Questions with Descriptive Statistics |
Diana D. Suhr |
source |
7 |
| WUSS |
2010 |
Answering Your Research Questions with Inferential Statistics |
Diana D. Suhr |
source |
10 |
| WUSS |
2010 |
Getting Started with SAS OnDemand for Academics: Enterprise Miner |
Gerardo Perez-Lizarraga |
source |
9 |
| WUSS |
2010 |
Graphing a Progression of Time Series Plots |
Nathaniel Derby |
source |
9 |
| WUSS |
2010 |
Statistical Analysis - The First Steps |
Jennifer L. Waller |
source |
20 |
| PHUSE EU |
2010 |
A Case Study in Using Unit Testing as a Method of Primary Validation |
Ross Farrugia |
source
presentation source |
12 |
| PHUSE EU |
2010 |
BeST - Bioequivalence Study Template |
Pekka Heikkilä |
source
presentation source |
9 |
| PHUSE EU |
2010 |
Defining "Compliance" for Analysis Data |
Chris Decker,
Randall Austin |
source
presentation source |
7 |
| PHUSE EU |
2010 |
Exploratory Data Analysis in Pharmacogenomics Using SAS JMP and Windows WF Workflows |
Robert Eric Huisden |
source
presentation source |
4 |
| PHUSE EU |
2010 |
How can we do things better: A SAS Java Library Proposal and other stories |
Michael Auld |
source |
4 |
| PHUSE EU |
2010 |
How to clean up dirty data in Patient reported outcomes? |
Knut Mueller |
source
presentation source |
6 |
| PHUSE EU |
2010 |
How to go From an SDTM Findings Domain to an ADaM-Compliant Analysis Dataset: An Example |
Carl Herremans |
source
presentation source |
8 |
| PHUSE EU |
2010 |
Identifying medications that are protocol violations |
John van Bemmelen |
source
presentation source |
5 |
| PHUSE EU |
2010 |
Interactive Clinical Data Review for Safety Assesment and Trial Operations Management |
Michael O'Connell |
source
presentation source |
13 |
| PHUSE EU |
2010 |
Statistical Graphics for Review and Reporting in Clinical Development |
Kerstin Pietzko,
Michael O'Connell |
source
poster source |
12 |
| PHUSE EU |
2010 |
Traceability between SDTM and ADaM converted analysis datasets |
Florence Somers,
Michael Knoessl |
source
presentation source |
7 |
| PHUSE EU |
2010 |
Validation Strategies for Report Objects and Programs - Challenges and Obstacles in a Risk Based World |
Christoph Ziegler,
Beate Hientzsch |
source
presentation source |
12 |
| MWSUG |
2010 |
Application Development with SAS Stored Processes |
John Xu |
|
38 |
| MWSUG |
2010 |
Applied Revolutionary BI |
Charles D. Kincaid |
|
16 |
| MWSUG |
2010 |
Comparing JMP and SAS for Validating Clinical Trials |
Sandra D. Schlotzhauer |
|
18 |
| MWSUG |
2010 |
Exploring, Analyzing, and Summarizing Your Data: Choosing and Using the Right SAS Tool from a Rich Portfolio |
Douglas Thompson |
|
25 |
| MWSUG |
2010 |
Macrotize! A Beginner's Guide to Designing and Writing Macros |
Stacey D. Phillips |
|
12 |
| MWSUG |
2010 |
Salesforce Effectiveness at Sears: An Analytic Approach to Goal Setting and Tracking |
Carl Schleyer,
Jason Chavarry |
|
5 |
| MWSUG |
2010 |
Using the JMP 9 R Interfaces to Perform Bayesian Analyses: Why, How, and What |
Dave LeBlond |
|
18 |
| SESUG |
2010 |
A Taste of ADaM |
Beilei Xu |
source |
9 |
| SESUG |
2010 |
Recoding "ALL THAT APPLY" Variables from Handhelds and Portable Computers |
Wafa Handley,
Barbara Bibb,
Lilia Filippenko,
Jay Levinsohn,
Donna Medeiros |
source |
7 |
| SESUG |
2010 |
Statistical Analysis - The First Steps |
Jennifer L. Waller |
source |
20 |
| PharmaSUG |
2010 |
Clinical Programming For Novice |
Ramesh Ayyappath |
|
5 |
| PharmaSUG |
2010 |
Help! The EX Domain is Now an Analysis Dataset! What Do I Do?!? |
David C. Izard |
|
4 |
| PharmaSUG |
2010 |
How to build ADaM from SDTM: A real case study |
Jian Hua (Daniel) Huang |
|
12 |
| PharmaSUG |
2010 |
Insights into ADaM |
Matthew J. Becker |
|
9 |
| PharmaSUG |
2010 |
Lessons Learned as a SAS Programming Lead Across Cultures |
Eunice Ndungu |
|
5 |
| PharmaSUG |
2010 |
The CDISC/FDA Integrated Data Pilot: A Final Summary of Findings, Reviewer Feedback, and Recommendations Implementing CDISC Standards Within and Across Studies |
Chris Decker |
|
20 |
| SGF |
2010 |
dATa qWaliti 4 Analytics |
David Barkaway,
Gerhard Svolba |
source |
12 |
| SGF |
2010 |
Efficient Statistical Programming? Reducing SAS Run Time with WHERE Setup |
Keiko I. Powers |
source |
4 |
| SGF |
2010 |
Research in Agriculture |
Rogerio C. Traballi,
Ieda K. Makiya |
source |
1 |
| SGF |
2010 |
Using New JMP Interactive Modules to Teach Concepts in Introductory Statistics |
Amy G. Froelich,
William M. Duckworth |
source |
9 |
| SESUG |
2009 |
A Little Stats Won't Hurt You |
Nathaniel Derby |
source |
18 |
| SESUG |
2009 |
Customer Retention Predictive Modeling in HealthCare Insurance Industry |
Jin Su,
Kimberly Cooper,
Tina Robinson,
Brad Jordan |
source |
8 |
| SESUG |
2009 |
Streamlining Data Analysis |
Edzard van Santen |
source |
4 |
| PHUSE EU |
2009 |
Clinical Database acceptance: what statistical review checks are necessary to validate a database? |
Genevieve Jehl |
source |
12 |
| PHUSE EU |
2009 |
ClinicalTrials.gov - a programmers perspective |
Ralf Minkenberg |
source
presentation source |
6 |
| PHUSE EU |
2009 |
Data review: To see or not to see.. |
Estelle Tiemtore |
source
presentation source |
6 |
| PHUSE EU |
2009 |
Database/Biostatistics Audits - from the Auditor's Perspective |
Barry Ryan |
source
presentation source |
7 |
| PHUSE EU |
2009 |
Implementation of CDISC Standards at Nycomed [presentation] |
Berthold Traub |
source |
31 |
| PHUSE EU |
2009 |
Insights into ADaM |
Matthew J. Becker |
source
presentation source |
9 |
| PHUSE EU |
2009 |
Managing your metadata efficiently |
Kirsten Langendorf,
Mikkel Traun |
source |
12 |
| PHUSE EU |
2009 |
Metadata and Standard Programs |
Marianne Carames,
Martin Lindhard |
source
presentation source |
10 |
| PHUSE EU |
2009 |
On the use of spreadsheets for statistical analysis |
Martin Gregory |
source |
7 |
| PHUSE EU |
2009 |
Pharmaceutical expectations and CRO expectations - how can we best get them to agree? |
Karen Turner,
Esther Bayon |
source |
9 |
| PHUSE EU |
2009 |
Requirements, Specifications and Programming - How to ... cooperate with Statisticians in an effective way ... accelerate the production of report objects ... create technical specifications out of programs |
Christoph Ziegler |
source
presentation source |
8 |
| PHUSE EU |
2009 |
The CDISC/FDA Integrated Data Pilot: A Case Study in Implementing CDISC Standards to support an Integrated Review |
Chris Decker |
source
presentation source |
15 |
| MWSUG |
2009 |
A Little Stats Won't Hurt You |
Nathaniel Derby |
|
18 |
| PNWSUG |
2009 |
A Little Stats Won't Hurt You |
Nathaniel Derby |
|
18 |
| PNWSUG |
2009 |
Wait Wait, Don't Tell Me… You're Using the Wrong Proc! |
David L. Cassell |
|
11 |
| NESUG |
2009 |
A Proposed SDTM Implementation of Response Data for Solid Tumor Trials in Oncology |
Mei Dey,
Elisabeth Pyle |
|
18 |
| NESUG |
2009 |
LOCF: It's more than just carrying forward |
Vikash Jain,
Niraj J. Pandya |
|
10 |
| NESUG |
2009 |
Process Excursion Detection using Statistical Analysis Methodologies in High Volume Semiconductor Production |
Peter Frankwicz |
|
8 |
| NESUG |
2009 |
Using Macros to Build a Robust, Data Driven Proc GLM |
Ginger Lewis,
Frank J. Tedesco |
|
9 |
| WUSS |
2009 |
A Little Stats Won't Hurt You |
Nathaniel Derby |
source |
18 |
| WUSS |
2009 |
Efficient Statistical Programming? - These Small Steps Make the Difference |
Keiko I. Powers |
source |
16 |
| PharmaSUG |
2009 |
A Little Stats Won't Hurt You |
Nathaniel Derby |
|
18 |
| PharmaSUG |
2009 |
A Statistical Analysis System for Categorical Data using SAS |
Cheng Jun Tian |
|
10 |
| PharmaSUG |
2009 |
ARROW Clinical Data Analysis System: An Integration of Statistical Analysis and Reporting |
Cheng Jun Tian,
Denis Michel |
|
9 |
| PharmaSUG |
2009 |
Arrow Statistical Graphic System |
Cheng Jun Tian,
Qin Li,
Jiangfan Li |
|
15 |
| PharmaSUG |
2009 |
Concepts and Ideas for Developing and Maintaining a Utility Toolbox of SAS Statistical Procedures |
David W. Carr |
|
6 |
| PharmaSUG |
2009 |
Empowering SAS Programmers: The Role of the Manager |
Carey G. Smoak |
|
3 |
| PharmaSUG |
2009 |
Image is Almost Everything: Displaying Statistics Via ODS |
R. Scott Leslie |
|
8 |
| PharmaSUG |
2009 |
Implementation Plan for CDISC SDTM & ADaM Standards at MedImmune |
Alan Meier |
|
11 |
| PharmaSUG |
2009 |
Oracle Clinical for SAS Programmers |
Kevin Lee |
|
8 |
| PharmaSUG |
2009 |
Statistics for Clinical Trial SAS Programmers 1: paired t-test |
Kevin Lee |
|
6 |
| PharmaSUG |
2009 |
Technical Support in Biometrics |
Wei Dong |
|
4 |
| SGF |
2009 |
A Discussion of Various Possibilities for Data Entry Using SAS: An Evergreen |
Barbara Schneider,
Kristan A. Schneider |
source |
11 |
| SGF |
2009 |
A Little Stats Won't Hurt You |
Nathaniel Derby |
source |
17 |
| SGF |
2009 |
Comparison of Features and Applications of Four Linear Models Procedures |
Larry W. Douglass |
source |
19 |
| SGF |
2009 |
Getting the Most Out of the SAS Survey Procedures: Repeated Replication Methods, Subpopulation Analysis, and Missing Data Options in SAS 9.2 |
Patricia A. Berglund |
source |
12 |
| SGF |
2009 |
Image is Almost Everything: Displaying Statistics Via ODS |
R. Scott Leslie |
source |
8 |
| SGF |
2009 |
Let Me Look At It! Graphic Presentation of Any Numeric Variable |
Anastasiya M. Osborne |
source |
12 |
| SGF |
2009 |
SAS Enterprise Guide for the Business Analyst |
Lina Clover |
source |
11 |
| SGF |
2009 |
Source of Nitrogen in Q-BOP Steel (Statistical Analysis) |
Arkady M. Kushnir |
source |
19 |
| SGF |
2009 |
The Increased Utilization of Analytics and How Academic Programs Are Responding to Job Market Demands by Leveraging Predictive Modeling with SAS Enterprise Miner Certification |
Goutam Chakraborty,
Julie Petlick |
source |
4 |
| SGF |
2009 |
Using GEE to Model Student's Satisfaction: A SAS Macro Approach |
Teck Kiang Tan,
Trivina Kang,
David Hogan |
source |
12 |
| WUSS |
2008 |
An Unaccusative Categorization of 'Swarm' Type Verbs in Spanish: An Application of SAS to Linguistic Research |
Roberto Mayoral Hernández,
Lindsey N. Chen |
source |
6 |
| WUSS |
2008 |
Efficient Statistical Programming? - Let's Work on Those Data Steps First |
Keiko I. Powers |
source |
4 |
| WUSS |
2008 |
Evaluation of a Hospice Care Referral Program Using Cox Proportional Hazards Model |
Lida Gharibvand,
Daniel R. Jeske,
Solomon Liao |
source |
16 |
| WUSS |
2008 |
Image is Almost Everything: Displaying Statistics Via ODS |
R. Scott Leslie |
source |
5 |
| WUSS |
2008 |
Moving from Data to Information: SAS Programming to Reduce Statistical and Programming Errors |
AnnMaria De Mars |
source |
6 |
| WUSS |
2008 |
Quick and Complete Statistical Analyses Using SAS Enterprise Guide |
George C. J. Fernandez |
source |
3 |
| WUSS |
2008 |
Statistical Analysis of Source of Nitrogen in Q-BOP Steel |
Arkady M. Kushnir |
source |
10 |
| WUSS |
2008 |
Step your way through Path Analysis |
Diana D. Suhr |
source |
10 |
| SESUG |
2008 |
Complex Survey Data Analysis in SAS and the Link between PROC SURVEYFREQ and SURVEYMEANS |
Taylor Lewis |
source |
5 |
| SESUG |
2008 |
Data Manipulations Using Arrays and DO Loops |
Patricia Hall,
Jennifer L. Waller |
source |
9 |
| SESUG |
2008 |
Let Me Look At It! Graphic Presentation of Any Numeric Variable |
Anastasiya M. Osborne |
source |
11 |
| SESUG |
2008 |
SAS Graphics on ODS 9.2 Performance-Enhancing Steroids |
Daniel O'Connor |
source |
18 |
| SESUG |
2008 |
Techniques for Developing Quality SAS Macros |
Ginger Redner,
Liping Zhang,
Carl Herremans |
source |
11 |
| SESUG |
2008 |
Using SAS to Analyze Longitudinal Study |
Abbas S. Tavakoli |
source |
13 |
| PHUSE EU |
2008 |
A Graphical Approach to Examine the Completeness of Epidemiological Data: Patient Profile Plots (PPPs) and Centre Profile Plots (CPPs) |
Methodios Typou,
Joseph Kim |
source |
14 |
| PHUSE EU |
2008 |
Challenges and Opportunities of working with the Pharma industry - A BPO perspective |
K. V. Palanichamy,
Samidha Sawant |
source |
7 |
| PHUSE EU |
2008 |
Concepts and Ideas for Developing and Maintaining a Utility Toolbox of SAS Statistical Procedures |
David W. Carr |
source |
6 |
| PHUSE EU |
2008 |
Data Standardisation, Clinical Data Warehouse and SAS Standard Programs |
Jean-Marc Ferran,
Mikkel Traun |
source |
8 |
| PHUSE EU |
2008 |
Delivering Statistics - a Workflow Supported by the SAS Stored Processes |
Volker Harm |
source |
8 |
| PHUSE EU |
2008 |
Efficiency Issues in Evaluating Pharmacogenetic Data With SAS |
Volker Harm,
Stephan Lehr |
source |
10 |
| PHUSE EU |
2008 |
Exchange of Information for the Statistical Analysis and Reporting of PK Parameter Data |
Ann Cuijpers,
Sarah Rusch |
source |
2 |
| PHUSE EU |
2008 |
RECIST Temptation |
Paul Jenkins |
source |
8 |
| PHUSE EU |
2008 |
Spot the Difference |
Anja Feuerbacher,
Beate Hientzsch |
source |
13 |
| PHUSE EU |
2008 |
Statistically guided review of safety data in clinical trials |
Michael O'Connell,
Harry Southworth |
source |
12 |
| PHUSE EU |
2008 |
Styling statistical output - A CRO perspective |
Annet te Velde |
source |
8 |
| PHUSE EU |
2008 |
Titles and footnote management from the TLF shell to the final outputs |
Thierry Jegoux |
source |
10 |
| MWSUG |
2008 |
Chemical Informatics using JMP PowerMV and ChemModLab |
S. Stanley Young,
Thomas H. Burger,
Michael S. Lajiness,
Wolf-D. Ihlenfeldt |
|
40 |
| MWSUG |
2008 |
Getting Started with ODS Statistical Graphics in SAS 9.2 |
Robert N. Rodriguez |
|
21 |
| MWSUG |
2008 |
Let Me Look At It! Graphic Presentation of Any Numeric Variable |
Anastasiya M. Osborne |
|
11 |
| MWSUG |
2008 |
Mastectomy Versus Lumpectomy In Breast Cancer Treatment |
Beatrice Ugiliweneza |
|
17 |
| MWSUG |
2008 |
P Charts for Improved Analysis |
Vin Kane |
|
16 |
| PNWSUG |
2008 |
Introduction to Clinical Trials in Pharmaceutical Industry - From a SAS Programmer's Point of View [presentation] |
Wenyun Ji |
|
19 |
| PNWSUG |
2008 |
Wait Wait, Don't Tell Me… You're Using the Wrong Proc! |
David L. Cassell |
|
11 |
| NESUG |
2008 |
Develop A Demographic Data Analysis Report System By SAS and Visual Basic |
Richard Zhou |
|
13 |
| NESUG |
2008 |
Guido's Guide to PROC MEANS - A Tutorial for Beginners Using the SAS System |
Joseph J. Guido |
|
11 |
| NESUG |
2008 |
SAS Graphics on ODS 9.2 Performance-Enhancing Steroids |
Daniel O'Connor |
|
18 |
| NESUG |
2008 |
Tricks to Quickly Analyze and Graphically Represent Numeric Data |
Anastasiya M. Osborne |
|
9 |
| PharmaSUG |
2008 |
A SAS Macro for Single Imputation |
Shuping Zhang,
Jane X. Liao,
Xingshu Zhu |
|
8 |
| PharmaSUG |
2008 |
Empowering SAS Programmers to Meet Deadlines |
Carey G. Smoak |
|
3 |
| PharmaSUG |
2008 |
Facilitate Statistical Analysis with Automatic Collapsing of Small Size Strata |
Sunil Kumar Gupta,
Linfeng Xu,
Thousand Oaks |
|
12 |
| PharmaSUG |
2008 |
Managing Operational Challenges for Interim Analyses |
Mei Dey |
|
10 |
| PharmaSUG |
2008 |
Moving a Project Team Out of the Crisis and onto Problem Solving: An Approach to Facilitating Risk Analysis |
Sandy Paternotte |
|
6 |
| PharmaSUG |
2008 |
Sample Size Estimation Through Simulation of a Random Coefficient Model by Using SAS |
Junliang Chen,
Shannon Stock,
Chunqin Deng |
|
8 |
| PharmaSUG |
2008 |
Strategies for Building an Effective Relationship with a Contract Research Organization |
Jackie Lane |
|
3 |
| PharmaSUG |
2008 |
The Power of PROC GPLOT in Statistical Analysis of Clinical Studies |
Aiming Yang |
|
13 |
| PharmaSUG |
2008 |
Using SAS Enterprise Guide 4.0 to find a Correlation between Mortality and Co-morbidities for Prostate Disease Patients |
Jeong W. Park |
|
18 |
| SGF |
2008 |
CSI: San Antonio - Common SAS Issues in Our Programs and Tips for Better Investigation of Your SAS Code |
Rachel Brown,
Jennifer K. Fulton |
source |
9 |
| SGF |
2008 |
Easy as Pie Charts (Any Way You Slice Em) |
Jonah P. Turner |
source |
12 |
| SGF |
2008 |
Getting Started with ODS Statistical Graphics in SAS 9.2 |
Robert N. Rodriguez |
source |
21 |
| SGF |
2008 |
Oracle Clinical for SAS Programmers |
Kevin Lee |
source |
8 |
| SGF |
2008 |
SAS Graphics on ODS 9.2 Performance-Enhancing Steroids |
Daniel O'Connor |
source |
18 |
| SGF |
2008 |
Technology Solutions to Detect Fraud and Counter Other IT Risks |
Eckhardt Kriel |
source |
12 |
| SGF |
2008 |
The Design, Development, and Implementation of a Control-Data Tracking and Analysis System for Immunoassays Using SAS/AF |
How J. Tsao,
Andrew McKeen,
Roger French,
Andrew S. Bascom,
Chunwei J. Kuo,
Khushroo E. Shroff |
source |
9 |
| SGF |
2008 |
The Evolution of SAS in Life Sciences Research and Development |
David Handelsman |
source |
10 |
| SGF |
2008 |
Using SAS as an Integrated Component of the Clinical Research Information System |
Christopher W. Schacherer,
Jeffrey E. Gershenwald |
source |
11 |
| NESUG |
2007 |
An Introduction to SAS Stat Studio: A Programmable Successor to SAS/INSIGHT |
Rick Wicklin,
Peter Rowe |
|
18 |
| NESUG |
2007 |
Common Pitfalls in SAS Statistical Analysis Macros in a Mass Production Environment |
Huei-Ling Chen,
Aiming Yang |
|
9 |
| SESUG |
2007 |
Data Mining Episode Groupers |
Patricia B. Cerrito |
source |
13 |
| SESUG |
2007 |
Integrating SAS and Microsoft .NET for Data Analysis |
Mai Nguyen,
Shane Trahan,
Patricia Nguyen,
Jonathan Cirella |
source |
10 |
| WUSS |
2007 |
Adding the Feature of Age Adjustment for the Survey-related Procedures of SAS - Age Adjusting Prevalence Estimates from Population Based Survey Datasets |
Zhiwei Zeng |
source |
6 |
| WUSS |
2007 |
An Introduction to SAS Stat Studio: A Programmable Successor to SAS/INSIGHT |
Rick Wicklin,
Peter Rowe |
source |
18 |
| WUSS |
2007 |
New SAS/GRAPH Procedures for Creating Statistical Graphics |
Cleester D. Heath |
source |
16 |
| WUSS |
2007 |
Time Series Cross Sectional Analysis of Total Nitrogen Concentration in Truckee River, Nevada Using SAS |
Anpalaki J. Ragavan |
source |
11 |
| WUSS |
2007 |
Wait Wait, Don't Tell Me… You're Using the Wrong Proc! |
David L. Cassell |
source |
11 |
| PHUSE EU |
2007 |
A dedicated programming group in a pharma M&S organization |
Vincent Buchheit |
source |
8 |
| PHUSE EU |
2007 |
Application of the ARRAY statement to create ESTIMATE and CONTRAST statements in statistical PROCEDURES: a case study |
Roel Straetemans |
source |
10 |
| PHUSE EU |
2007 |
Graph automation using integrated SAS/S-PLUS solution |
Qian Wang,
Carl Herremans |
source |
7 |
| PHUSE EU |
2007 |
LSLV to Final CSR Tables in 24 hours - Dream or Reality? |
Stinder Fowler |
source |
10 |
| PHUSE EU |
2007 |
Preparing real world data in Excel sheets for stats analysis |
Volker Harm |
source |
6 |
| SCSUG |
2007 |
An Introduction to SAS Stat Studio: A Programmable Successor to SAS/INSIGHT |
Rick Wicklin,
Peter Rowe |
|
18 |
| PNWSUG |
2007 |
Missing Data? A Look at Two Imputation Methods |
Anita Rocha |
|
8 |
| PharmaSUG |
2007 |
A Scalable Platform For Clinical Trials - Interoperability And Automation In A Web-Based Environment |
John R. Gerlach,
Maulik Shah |
|
11 |
| PharmaSUG |
2007 |
An Efficient Report Checking Method |
Xuejing (Susan) Mao,
Mario Widel |
|
7 |
| PharmaSUG |
2007 |
Automate Data Integration Processes for Pharmaceutical Data Warehouse |
Sandy Lei |
|
7 |
| PharmaSUG |
2007 |
Automatic Creation of Analysis Datasets for Clinical Trials - A Macro Program |
John H. Adams |
|
17 |
| PharmaSUG |
2007 |
Challenge the Specs |
Catherine Edwards |
|
7 |
| PharmaSUG |
2007 |
CSI - Denver: Common SAS Issues in Our Programs and Tips for Better Investigation of Your SAS Code |
Rachel Brown |
|
9 |
| PharmaSUG |
2007 |
Developing Reporting & Analysis Methodologies |
Amy Gillespie,
Mary N. Varughese |
|
5 |
| PharmaSUG |
2007 |
From CRF Data to DEFINE.XML: Going "End to End" with Metadata |
Frank C. DiIorio,
Jeffrey M. Abolafia |
|
20 |
| PharmaSUG |
2007 |
Managing the CRO Relationship to Effectively Request and Receive CDISC STDM and ADaM Deliverables |
Kenneth Eng,
David C. Izard,
Terek J. Peterson |
|
8 |
| PharmaSUG |
2007 |
SAS Markov Chain Monte Carlo (MCMC) Simulation in Practice |
Shi-Tao Yeh,
Scott D Patterson |
|
20 |
| PharmaSUG |
2007 |
Techniques for Developing Quality SAS Macros |
Ginger Redner,
Liping Zhang,
Carl Herremans |
|
10 |
| SGF |
2007 |
Alternatives for Analysis of Complex Sample Surveys: A Comparison of SAS, SUDAAN, and AM Software |
Bethany A. Kromrey,
Jeffrey D. Bell-Ellison |
source |
10 |
| SGF |
2007 |
An Introduction to SAS Stat Studio: A Programmable Successor to SAS/INSIGHT |
Rick Wicklin,
Peter Rowe |
source |
18 |
| SGF |
2007 |
An Introduction to SAS Stat Studio: A Programmable Successor to SAS/INSIGHT |
Rick Wicklin,
Peter Rowe |
source |
18 |
| SGF |
2007 |
Delivering SAS to Excel Jockeys |
Sy J. Xu,
Jing Truong |
source |
10 |
| SGF |
2007 |
Gaining Power from GTL and ODS Style to Control Graphical Output |
Lea Guo,
Nan McCarthy,
William F. Liu |
source |
9 |
| SGF |
2007 |
New SAS/GRAPH Procedures for Creating Statistical Graphics in Data Analysis |
Dan Heath |
source |
16 |
| SGF |
2007 |
Repeated Measures Analysis with Clustered Subjects |
Ramon C. Littell |
source |
11 |
| SGF |
2007 |
The ABC's of Graphical Data Analysis Using SAS/GRAPH |
Hany Aboutaleb |
source |
11 |
| PNWSUG |
2006 |
Wait Wait, Don't Tell Me… You're Using the Wrong Proc! |
David L. Cassell |
|
11 |
| MWSUG |
2006 |
Deploying SAS as the Cornerstone of a Stability Monitoring Program |
Jeff Gardner |
|
9 |
| MWSUG |
2006 |
How to use Summary Statistics as raw data to do basic statistical analysis |
Dachao Liu |
|
6 |
| SCSUG |
2006 |
Data Mining at the Texas State Auditor's Office |
Thomas J. Winn Jr. |
|
11 |
| PHUSE EU |
2006 |
Integrating Specialized Graphics and Analysis into Production Systems |
Joel M. Hoffman,
Michael O'Connell |
source |
18 |
| PHUSE EU |
2006 |
Interfering with Data Management by the Statistician |
Jim Groeneveld |
source |
6 |
| PHUSE EU |
2006 |
Is your output telling you the truth? Tips and Tricks in verifying SAS Outputs |
Angelo Tinazzi,
Sonia Colombini |
source |
7 |
| PHUSE EU |
2006 |
Metrics Unleashed: Measuring Productivity or Inspiring Artisans |
Neil Howard,
Gregory S. Barnes Nelson |
source |
10 |
| PHUSE EU |
2006 |
Proc mixed -- Trials and Tribulations |
Shelley Fordred |
source |
7 |
| PHUSE EU |
2006 |
SAS Programmer Resources on the web: Experiences Acquired Surfing the Net |
Angelo Tinazzi,
Alessandro Cattaneo |
source |
9 |
| PHUSE EU |
2006 |
Save Time: Program Your Output Specs |
Hansjörg Frenzel,
James Witt |
source |
11 |
| PHUSE EU |
2006 |
Statistical Graphics and Reporting in Drug Development |
Michael O'Connell,
Sven Knudsen |
source |
13 |
| PHUSE EU |
2006 |
Tracking user requirements and output development |
Xavier Passera,
Jon-Paul Mewes |
source |
11 |
| SESUG |
2006 |
ST09 Application of the Generalized Linear Model to the Prediction of Lung Cancer Survival |
Andrew Karem |
source |
18 |
| WUSS |
2006 |
Creating Statistical Graphics in SAS 9.2: What Every Statistical User Should Know |
Robert N. Rodriguez,
Tonya E. Balan |
source |
32 |
| WUSS |
2006 |
Enterprise Guide for Business Analysts |
Sunil Kumar Gupta |
source |
10 |
| WUSS |
2006 |
Have It Both Ways: Macros that Produce Publication-Quality Tables and Stand-alone Code |
Linda Collins,
Lisa Kaye Brooks,
Michael Rea,
Alan Hopkins |
source |
19 |
| WUSS |
2006 |
Sample Survey Data and the Procs you OUGHT To Be Using |
David L. Cassell |
source |
13 |
| WUSS |
2006 |
Steps to Success with PROC MEANS |
Andrew H. Karp |
source |
12 |
| WUSS |
2006 |
Testing for Verb Types in Spanish: An Application of SAS to Corpus Linguistics |
Roberto Mayoral Hernández,
Lindsey N. Chen |
source |
6 |
| WUSS |
2006 |
The Basics of Structural Equation Modeling |
Diana D. Suhr |
source |
19 |
| WUSS |
2006 |
Wait Wait, Don't Tell Me… You're Using the Wrong Proc! |
David L. Cassell |
source |
11 |
| NESUG |
2006 |
Implementing SAS and Enterprise Guide to Enhance a Graduate Biostatistics Curriculum |
Albert Crawford,
Howard Chapman |
|
9 |
| NESUG |
2006 |
Using SAS to Analyze the Summary Data |
Zhenyi Xue |
|
6 |
| PharmaSUG |
2006 |
A Case of Online Data Processing and Statistical Analysis via SAS/IntrNet |
Sijian Zhang |
|
8 |
| PharmaSUG |
2006 |
Creating Statistical Graphics in SAS 9.2: What Every Statistical User Should Know |
Robert N. Rodriguez |
|
32 |
| PharmaSUG |
2006 |
Identifying the roles and responsibilities of programmers and statisticians in the planning, in-life and post-filing activities for a new drug or vaccine product |
Margaret James,
Amy Gillespie,
Ying Su,
William Malbecq |
|
6 |
| PharmaSUG |
2006 |
Managing Clinical Trials Data using SAS Software |
Martin J. Rosenberg |
|
7 |
| PharmaSUG |
2006 |
My Experience as a Facilitator Between Biostatisticians and SAS Programmers |
Carey G. Smoak |
|
3 |
| PharmaSUG |
2006 |
Searching for the Right Search Tool |
Eugene Yeh,
Angela S. Ringelberg |
|
12 |
| PharmaSUG |
2006 |
Transforming Business Requirements into System Solutions |
Yongcun Zhang |
|
10 |
| SUGI |
2006 |
%hlmdata and %hlmrmpower: Traditional Repeated Measures vs. HLM for Multilevel Longitudinal Data Analysis?Power and Type I Error Rate Comparison |
Hua Fang |
source |
11 |
| SUGI |
2006 |
Creating Statistical Graphics in SAS 9.2: What Every Statistical User Should Know |
Robert N. Rodriguez,
Tonya E. Balan |
source |
32 |
| SUGI |
2006 |
Exploratory or Confirmatory Factor Analysis? |
Diana D. Suhr |
source |
17 |
| SUGI |
2006 |
Fraud Detection - A Primer for SAS Programmers |
Thomas J. Winn Jr. |
source |
6 |
| SUGI |
2006 |
Introduction to SAS Enterprise Guide 4.1 for Statistical Analysis |
Charles B. Hallahan,
Linda P. Atkinson |
source |
22 |
| SUGI |
2006 |
Litigation Data Analysis/Auditing/ETL for BI: Triplets Separated at Birth |
Nicholson E. Warman |
source |
15 |
| SUGI |
2006 |
Processing Large Environmental Data Sets with SAS: Writing Robust and Dynamic SAS Macro Code |
Peter Mooney,
Conor McDonagh,
Adam C. Winstanley |
source |
7 |
| SUGI |
2006 |
SAS/OR - Making Sense of Network Data with Network Visualization Workshop |
Edward P. Hughes,
Phil Meanor |
source |
20 |
| SUGI |
2006 |
State Agency Personnel Information Reports: A SAS/IntrNet Project |
Thomas J. Winn Jr. |
source |
8 |
| SUGI |
2006 |
Using SAS for Statistical Modeling of Nutrient Removal and Water Quality Aspects from Constructed Wetlands |
Rupali Mohansingh,
George C. J. Fernandez,
Keith E. Dennett |
source |
11 |
| SUGI |
2006 |
Using Statistical Graphics to Understand Your Data (Not Just to Present Results) |
David J. Pasta |
source |
14 |
| SUGI |
2006 |
Wait Wait, Don't Tell Me… You're Using the Wrong Proc! |
David L. Cassell |
source |
11 |
| PNWSUG |
2005 |
SAS Enterprise Guide for the MBA Student-No Longer a Hard Sell |
Melvin Ott |
|
4 |
| PHUSE EU |
2005 |
An Introduction to CDISC - CDISC Collaborations and Standards in Progress |
Becky Kush |
source |
46 |
| PHUSE EU |
2005 |
Customer oriented CDISC implementation |
Edelbert Arnold,
Ulrike Plank |
source
poster source |
13 |
| PHUSE EU |
2005 |
Macro MDU: a flowchart of used programs, datasets and TLF's based upon the Final Run |
Herman Ament |
source |
10 |
| PHUSE EU |
2005 |
Managing Clinical Trials Data using SAS |
Martin J. Rosenberg |
source |
7 |
| PHUSE EU |
2005 |
Regulatory Compliant Validation and Deployment of SAS Programs with the Colibri Server |
Andreas Mangold |
source |
7 |
| PHUSE EU |
2005 |
The European System for Monitoring Drug Safety, EudraVigilance |
Hans-Georg Wagner,
Olivier Simoen |
source |
13 |
| PHUSE EU |
2005 |
The Future of CDISC |
Becky Kush |
source |
50 |
| MWSUG |
2005 |
Comparison Of Enterprise Miner And SAS/STAT For Data Mining |
Patricia B. Cerrito |
|
12 |
| MWSUG |
2005 |
Time Dependent Data Exploration And Preprocessing: Doing It All By SAS |
Joseph Twagilimana |
|
10 |
| WUSS |
2005 |
A Comparison of Missing Data Handling Methods |
Catherine Truxillo |
source |
20 |
| WUSS |
2005 |
A Programmer's Guide to Statistical Procedures |
Jim Edgington |
source |
4 |
| WUSS |
2005 |
Better Communication, Analysis and Decisions SAS plus GIS |
Stephen Trammell |
source |
4 |
| WUSS |
2005 |
Data Integrity through DEFINE.PDF and DEFINE.XML |
Sy J. Truong |
source |
14 |
| WUSS |
2005 |
Enterprise Guide for Business Analysts |
Sunil Kumar Gupta |
source |
13 |
| WUSS |
2005 |
Using Statistical Graphics to Understand Your Data (Not Just Present Results) |
David J. Pasta |
source |
5 |
| NESUG |
2005 |
A SAS Programmer's Guide to Project - and Program-Level Quality Control |
Paul Gorrell |
|
15 |
| NESUG |
2005 |
Adopting New Techniques: Statistical Procedures to Determine the Agreement between two Laboratory Methods |
Ashley Peterson,
Larry W. Douglass |
|
13 |
| NESUG |
2005 |
Introduction to SAS Enterprise Guide 3.0 for Statistical Analysis |
Charles B. Hallahan,
Linda P. Atkinson |
|
20 |
| PharmaSUG |
2005 |
A SAS Application for Analyzing Quality of Life data: NCIC-CTG Standard Method |
Don (Dongguang) Li |
|
5 |
| PharmaSUG |
2005 |
An Automated Reporting Application for Safety Sciences |
Fang Dong |
|
9 |
| PharmaSUG |
2005 |
Comparison of Techniques for XML and RTF Tables |
Linda Collins |
|
15 |
| PharmaSUG |
2005 |
Designing Helpful Audit Trails |
John Gorden |
|
6 |
| PharmaSUG |
2005 |
Pharmaceutical Programming: From CRFs to Tables, Listings and Graphs, a process overview with real world examples |
Mark Penniston |
|
8 |
| PharmaSUG |
2005 |
Risk-Based Approach to SAS Program Validation |
Keith C. Benze |
|
7 |
| PharmaSUG |
2005 |
Statistical Table Specifications and Automatic Code Generation using XML |
Alan Hopkins,
Linda Collins |
|
7 |
| PharmaSUG |
2005 |
Strategies for Implementing SDTM and ADaM Standards |
Susan J. Kenny,
Michael A. Litzsinger |
|
8 |
| PharmaSUG |
2005 |
The Role of Analysis Datasets in Successful FDA Advisory Meetings |
Sandy Chang |
|
9 |
| PharmaSUG |
2005 |
To Macro or Not To Macro? |
Amy Gillespie,
Blue Bell |
|
8 |
| PharmaSUG |
2005 |
Using SAS to Automate The Process of Microarrays Data Normalization |
Lei Qin. Cancer |
|
7 |
| PharmaSUG |
2005 |
Validating Data Using SAS Formats as a Programming Tool |
John R. Gerlach |
|
11 |
| SUGI |
2005 |
A Microsoft Access GUI for SAS Automation |
Rubin Nan,
David Mullins |
source |
4 |
| SUGI |
2005 |
A SAS Framework for Network Security Intelligence |
Michael Protz,
Joe Zilka,
Jeff Mudd |
source |
16 |
| SUGI |
2005 |
Customizing ODS Statistical Graphics |
Shi-Tao Yeh |
source |
17 |
| SUGI |
2005 |
Introduction to SAS Enterprise Guide 3.0 for Statistical Analysis |
Charles B. Hallahan,
Linda P. Atkinson |
source |
20 |
| SUGI |
2005 |
Maximum Likelihood Parameter Estimation with Incomplete Data |
Catherine Truxillo |
source |
19 |
| SUGI |
2005 |
Model Building in PROC PHREG with Automatic Variable Selection and Information Criteria |
Emily M. Cain,
Ken Kleinman,
Ernest S. Shtatland |
source |
10 |
| SUGI |
2005 |
Rounding after Multiple Imputation with Non-Binary Categorical Covariates |
Christopher F. Ake |
source |
11 |
| SUGI |
2005 |
Statistical Analysis of Steel Formability |
Arkady M. Kushnir |
source |
12 |
| SUGI |
2005 |
Toward Effective Student Outcomes: Survey Data Analysis for Evaluation of School-Based Transdisciplinary Autism Teaming |
Wendy B. Dickinson,
Tanice Knopp |
source |
7 |
| NESUG |
2004 |
Clinical Trials Online - Running SAS on the Web Without SAS/IntrNet |
Quan Ren |
|
15 |
| NESUG |
2004 |
Graphical Display of Data - A Nonparametric Approach |
Shi-Tao Yeh |
|
18 |
| NESUG |
2004 |
Introduction to Using Enterprise Guide for Statistical Analysis |
Charles B. Hallahan,
Linda P. Atkinson |
|
19 |
| NESUG |
2004 |
Programming Techniques for Data Mining with SAS |
Samuel Berestizhevsky,
Tanya Kolosova |
|
14 |
| NESUG |
2004 |
SAS and Grid Computing - Maximize Efficiency, Lower Total Cost of Ownership |
Cheryl Doninger |
|
6 |
| SCSUG |
2004 |
Fraud Detection - A Primer for SAS Programmers |
Thomas J. Winn Jr. |
|
9 |
| WUSS |
2004 |
Applying Statistical Analysis to Improve Formability of Steel |
Arkady M. Kushnir |
source |
12 |
| WUSS |
2004 |
Are Religious Universities Religious?: A Multiple Regression Analysis of Varying Factors at Loyola Marymount University using SAS/ETS Procedures |
Jonathan Bingham,
Joel Shackelford |
source |
11 |
| WUSS |
2004 |
Package, Archive, Report and Test Statistical Models Using ODS |
Ted Clay |
source |
10 |
| WUSS |
2004 |
PROC GENMOD for Analysis of Correlated Outcome Data Using the LOGIT Link Function |
Tyler C. Smith,
Besa Smith,
William Honner,
Ming Ji |
source |
14 |
| WUSS |
2004 |
SAS and Grid Computing - Maximize Efficiency, Lower Total Cost of Ownership |
Cheryl Doninger |
source |
6 |
| WUSS |
2004 |
SAS Programming for the Pharmaceutical Industry |
Brian C. Shilling,
Carol Matthews |
source |
4 |
| WUSS |
2004 |
Successful FDA Advisory Meetings by using Analysis Datasets |
Sandy Chang,
Steven Wong |
source |
10 |
| MWSUG |
2004 |
Using SAS Enterprise Guide to Automate and Customize Statistical Analyses for Pharmaceutical Data |
Alex Dmitrienko,
Cindy Lee |
|
6 |
| PharmaSUG |
2004 |
"Haven't We Met Somewhere Before?" and Other Useful Lines (of code) to Get to Know Their Data (Version 2.0) |
David Rucker |
|
10 |
| PharmaSUG |
2004 |
2D-gel Proteomics in Biomarker Discovery |
Mark Carpenter,
Craig Rowell,
Heath McCorkle,
Coral Lamartiniere |
|
7 |
| PharmaSUG |
2004 |
Build Portable Structures and Programs for Electronic Regulatory Submissions |
Wei Cheng |
|
6 |
| PharmaSUG |
2004 |
Building a Powerful Clinical Decision Support System Using SAS/IntrNet |
Nick Pászty |
|
10 |
| PharmaSUG |
2004 |
CDX - clinical data management and report programming environment |
Gunilla Sköllermo,
Pål Edman |
|
7 |
| PharmaSUG |
2004 |
Generating N Shell Programs for N Reports in a Clinical Trial |
John R. Gerlach |
|
8 |
| PharmaSUG |
2004 |
Making Model Selection in Linear Mixed-Effects Models An Easy Process: A SAS Macro Procedure |
Henry Cheng,
Yuli Xie,
Elizabeth Reinbolt |
|
4 |
| PharmaSUG |
2004 |
Simultaneous Nonparametric Inference in a One-Way Layout Using the SAS System |
Paul Juneau |
|
17 |
| PharmaSUG |
2004 |
Statistical Application of SAS in Method Comparison Analysis |
David Shen |
|
13 |
| PharmaSUG |
2004 |
Testing Normality of Data using SAS |
Guangbin Peng |
|
6 |
| PharmaSUG |
2004 |
XML Data Mapping under SAS 9 - From the Perspective of Electronic Submissions |
Tianshu Li |
|
7 |
| SUGI |
2004 |
Clinical Trial Online - Running SAS on the Web without SAS/IntrNet |
Quan Ren |
source |
16 |
| SUGI |
2004 |
Introduction to Using SAS Enterprise Guide for Statistical Analysis |
Charles B. Hallahan,
Linda P. Atkinson |
source |
20 |
| SUGI |
2004 |
Make Your Data a Strategic Asset |
Ken Wright |
source |
8 |
| SUGI |
2004 |
SAS and Grid Computing - Maximize Efficiency, Lower Total Cost of Ownership |
Cheryl Doninger |
source |
7 |
| SUGI |
2004 |
SAS Backwards: Helping SAS and SPSS Students Speak the Same Language |
Joseph J. Guido,
Adam B. Rains |
source |
7 |
| SUGI |
2004 |
SAS Enterprise Guide - A Powerful Tool to Bridge the Gap between Statisticians and Medical Students |
Barbara G. Schneider,
Kristan A. Schneider |
source |
13 |
| SUGI |
2004 |
Steps to Success with PROC MEANS |
Andrew H. Karp |
source |
13 |
| WUSS |
2003 |
Answering Your Questions with Statistics |
Diana D. Suhr |
source |
6 |
| WUSS |
2003 |
Efficient Statistical Programming? Let's Be Creative With Those SAS Steps |
Keiko I. Powers |
source |
7 |
| WUSS |
2003 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
source |
6 |
| WUSS |
2003 |
JMP Ap.Dev Repository |
Charles E. Shipp,
Kirk Paul Lafler |
source |
3 |
| WUSS |
2003 |
Using SAS IN Educational Research |
Leping Liu |
source |
6 |
| SCSUG |
2003 |
Documentation and Accountability: Why Your SAS Programming Projects Can Benefit from Implementing a System Development Life Cycle (SDLC) |
Jennifer K. Fulton,
Stephen Black |
|
5 |
| SESUG |
2003 |
An Analysis Tool for Reviewing Farm Economic Data Using SAS/AF |
Van Johnson |
source |
7 |
| SESUG |
2003 |
Methods of Dealing with Values Below the Limit of Detection using SAS |
Carry W. Croghan,
Peter P. Egeghy |
source |
5 |
| SESUG |
2003 |
SD17 Preparing Data Using PROC SQL and SAS Macro for Paired Sample Comparison on Intervention Study |
Wei Zhao |
source |
4 |
| SESUG |
2003 |
Special Education Practice and Policy: What Principals Know and Need to Know |
Wendy B. Dickinson,
Tanice Knopp,
Janice Fauske |
source |
7 |
| SESUG |
2003 |
Too Many Choices! The IMPORTANCE of Rank-Ordering Independent Variables Prior to Exploratory Data Analysis |
Gregg Weldon |
source |
5 |
| MWSUG |
2003 |
Addressing 21 CFR Part 11 Concerns with Execution and Repository Control |
Curt Wehrley,
Donald L Penix Jr.,
Wing Lam |
|
8 |
| MWSUG |
2003 |
Using the SAS Statistical Tool from Thesis to Career: Current Experiences and Future Outlook |
Jean Chen |
|
3 |
| NESUG |
2003 |
Better Information Through Better Displays: The Full Monty |
Suzanne Cross |
|
4 |
| NESUG |
2003 |
Using Cluster Analysis for Retail Portfolio Segmentation in an Economic Capital Model: Homogeneity by Common Default Behavior Over Time |
Shannon Kelly |
|
12 |
| SEUGI |
2003 |
A Simplified Customer Analysis System for Millions of Telecom Customers Leveraging Analytical SAS Software [presentation] |
Tomoko Shibata |
source |
26 |
| SEUGI |
2003 |
An Analytical CRM System to support Telecom Italia Marketing Actions [presentation] |
Maria Luisa Pensa |
source |
33 |
| SEUGI |
2003 |
An Introduction to Genomics and SAS Scientific Discovery Solutions [presentation] |
Karen Miller |
source |
34 |
| SEUGI |
2003 |
Data Analysis in Supervision of Customs Adminstration:Enforcement Assessing System [presentation] |
Fang Bin |
source |
31 |
| SEUGI |
2003 |
Data Modelling in SAS - How SAS is Used for Research and Teaching to Enable Students to Become More Marketable [presentation] |
Iveta Stankovicova |
source |
30 |
| SEUGI |
2003 |
Drug Approval, making the best treatments available safely, but quickly - using SAS at the heart of generic reporting systems. [presentation] |
Jonathan Chainey,
Rob Horton |
source |
25 |
| SEUGI |
2003 |
Optimizing Fraud Management Systems [presentation] |
Henrik Wagner,
Pushkar Bhat |
source |
29 |
| SEUGI |
2003 |
Revenue Assurance in the telecommunication industry [presentation] |
Per Grosskopf |
source |
19 |
| SEUGI |
2003 |
SAS Human Capital Management [presentation] |
Carolyn Cobb |
source |
30 |
| SEUGI |
2003 |
Situational Management Center [presentation] |
Natalia Gourkova |
source |
18 |
| SEUGI |
2003 |
The Data Warehouse Methodology as an input for Data Mining Analysis in Public Health Service [presentation] |
Nathalie Coue |
source |
51 |
| SEUGI |
2003 |
Using the SAS System for Teaching and Research - A Short Review of Co-operations between Statisticians and Medical Students [presentation] |
Barbara G. Schneider |
source |
59 |
| PharmaSUG |
2003 |
A SAS Macro to Automate The Covariance Structure Determination in Repeated Measures Data Analysis with Mixed Procedure |
Don (Dongguang) Li |
|
4 |
| PharmaSUG |
2003 |
An Useful Chart of the Global Assessment in Clinical Trials |
Zhongwei Zhou |
|
4 |
| PharmaSUG |
2003 |
CDISC, ADaM, and TTE: What Are These Acronyms and How Can They Help Me with My Filing? |
Sandra Minjoe,
Judy Phelps |
|
4 |
| PharmaSUG |
2003 |
Clinical Data Model and FDA/CDISC Submissions |
Mark Edwards,
Gajanan Bhat |
|
10 |
| PharmaSUG |
2003 |
Defining a Validation Process for End-user (Data Manager/Statisticians) SAS Programs |
Andrew Lawton |
|
6 |
| PharmaSUG |
2003 |
Developing "EXSAS" an integrated system for statistical analysis of non-clinical experimental data using animals |
Chikuma Hamada |
|
6 |
| PharmaSUG |
2003 |
Statistical Processing and Analysis of Proteomic and Genomic Data |
Mark Carpenter,
Sreelatha Melath,
Sijian Zhang,
William E. Grizzle |
|
4 |
| PharmaSUG |
2003 |
Techniques to Create a Standard Folder Structure in a Windows NT/XP Share Area for Submission Projects and Their Protocols |
Share Area |
|
6 |
| PharmaSUG |
2003 |
Using RTF, EPS and PDFMARK to Automate the Creation of Your DEFINE.PDF Document for Electronic Submissions |
Dirk Spruck,
Aventis Behring |
|
6 |
| PharmaSUG |
2003 |
You've Got Data! : Using SAS from Data Receipt to Reporting |
Philip Vecchione |
|
8 |
| SUGI |
2003 |
Introduction to JMP |
Thomas A. Little |
source |
3 |
| SUGI |
2003 |
Reliability, Exploratory and Confirmatory Factor Analysis for the Scale of Athletic Priorities |
Diana D. Suhr |
source |
7 |
| SCSUG |
2002 |
Using the SAS System as an Audit Support Tool |
Thomas J. Winn Jr.,
Kirby L. Cossey,
Ernest Cuellar,
Olin Davis,
Dorvin Handrick,
Joyce Inman |
|
4 |
| NESUG |
2002 |
Clinical Trial Online - Running SAS on the Web without SAS/IntrNet |
Quan Ren |
|
7 |
| NESUG |
2002 |
Efficiency and Quality Control in the Preparation of a Preparing Statistical Review Aid in FDA e-Submissions |
James Wu,
Frederick A. Cieri,
Amy Gillespie |
|
4 |
| NESUG |
2002 |
Quality Control As Data Analysis |
Paul Gorrell |
|
7 |
| NESUG |
2002 |
Visual Optimization: Using SAS And Java To Explore High Density Data In Equity Portfolios |
Haftan M. Eckholdt,
Ezra Benun |
|
5 |
| NESUG |
2002 |
You've Got Data! Data Receipt and Reporting Using SAS |
Philip Vecchione |
|
8 |
| SESUG |
2002 |
Focusing Healthcare Quality Improvement Dollars: Using SAS' for Geographic Targeting |
Barbara B. Okerson,
Charlotte F. Carroll |
source |
7 |
| SESUG |
2002 |
The Essential Meaning of PROC MEANS: A Beginner's Guide to Summarizing Data Using SAS Software |
Andrew H. Karp,
Gary M. McQuown |
source |
10 |
| SESUG |
2002 |
Using Strategic Performance Management to Create Balanced Scorecards in a Healthcare Environment |
Ben Cochran |
source |
5 |
| WUSS |
2002 |
Generation of a Clinical Data Warehouse across Multiple Companies |
Sarbjit Rai |
source |
4 |
| WUSS |
2002 |
Imputation Strategies for Sexual Orientation Using SAS PROC MI |
Jesse Albert Canchola,
Joe Catania,
Torsten Neilands |
source |
6 |
| WUSS |
2002 |
Reliability, Exploratory, & Confirmatory Factor Analysis for the Scale of Atheletic Priorities |
Diana D. Suhr |
source |
8 |
| WUSS |
2002 |
The SAS Powered PDA |
David Bell,
Lynn G. Palmer |
source |
5 |
| WUSS |
2002 |
You've Got Data, Now What? |
Diana D. Suhr |
source |
3 |
| SEUGI |
2002 |
A www psychological quest using SAS [presentation] |
Bernard Pirali,
Michel Lehon,
Olivier Lebon,
Samuel Dupont,
Serge Roberfroid,
Sylvie Linotte |
source |
21 |
| SEUGI |
2002 |
bioWORKS - Easy Calculatio of FDA consistent Bioequivalence [presentation] |
Justo Lorenzo Bermejo |
source |
32 |
| SEUGI |
2002 |
Developing an infrastructure for the Efficient Use of SAS at the Federal Statistical Office Germany [presentation] |
Heinz Stralla |
source |
21 |
| SEUGI |
2002 |
Netarget - intelligence creation as core business process [presentation] |
Christophe Cousin |
source |
20 |
| SEUGI |
2002 |
OLAP Business Metrics Library - Tailored Analyses for Retailers' Mass Data and complex Business Figures [presentation] |
Sven Viergutz |
source |
23 |
| SEUGI |
2002 |
SAS and the CRO [presentation] |
Peter Stagg |
source |
14 |
| SEUGI |
2002 |
SAS Drug Development: Intelligent Research Management [presentation] |
Andrew T. Fagan |
source |
18 |
| SEUGI |
2002 |
Terabyte-class data analysis for CRM in service provider [presentation] |
Ryo Mukae |
source |
18 |
| SEUGI |
2002 |
Web & Data Warehouse to evaluate and control activities of Regione Piemonte Cancer Screening Programs [presentation] |
Corrado Marozzo,
Patrick Jegou |
source |
44 |
| PharmaSUG |
2002 |
Clinical Trial Online - Running SAS on the Web without SAS/IntrNet |
Quan Ren |
|
8 |
| PharmaSUG |
2002 |
MacStat: A Statistical Analysis and Reporting System using SAS Macros, Visual Basic, and Microsoft Word |
Richard Thomas |
|
6 |
| PharmaSUG |
2002 |
Preparing the SAS Software Programming Environment for Regulatory Submission |
Sunil Kumar Gupta |
|
10 |
| PharmaSUG |
2002 |
Rapid Assessment of Data Set Structures |
Philip Vecchione |
|
4 |
| SUGI |
2002 |
Clinical Trial Online - Running SAS on the Web without SAS/IntrNet |
Quan Ren |
source |
7 |
| SUGI |
2002 |
Data Entry Using SAS - A Discussion of Various Possibilities |
Barbara G. Schneider |
source |
|
| SUGI |
2002 |
Discriminant Analysis, A Powerful Classification Technique in Data Mining |
George C. J. Fernandez |
source |
9 |
| SUGI |
2002 |
Easy Access to Public Health Data Colorado Health Information Dataset (CoHID) |
Huiyun Xiang |
source |
3 |
| SUGI |
2002 |
Unit-of-Analysis Programming |
Vanessa C. Hayden |
source |
6 |
| NESUG |
2001 |
Analyzing Network Management Data with the SAS System |
Tracy L. Lord,
Charles E. Keeler |
|
3 |
| NESUG |
2001 |
Leaping Nodes in a Single Bound: Supporting SAS MP CONNECT with Windows 2000 Advanced Server |
Carol A. Murphree |
|
5 |
| NESUG |
2001 |
Lost in Space: Recovering unmeasured dimensions in spatial studies |
Haftan M. Eckholdt |
|
8 |
| NESUG |
2001 |
MacStat: A Statistical Analysis and Reporting System using SAS Macros, Visual Basic, and Microsoft Word |
Richard Thomas |
|
6 |
| NESUG |
2001 |
The Marriage of EDA & Mapping Techniques for the Analysis/Display of Census Data. |
Dave L. DesJardins |
|
8 |
| NESUG |
2001 |
The New User Interface of V9 Graphing Tools: A Usability Case Study |
Frank Wimmer |
|
4 |
| NESUG |
2001 |
Using SAS to Read Data Sets with Complicated Layouts |
Rebecca Goldblatt |
|
3 |
| SESUG |
2001 |
Evaluating the Use of Enterprise Guide in Introductory Statistics Classes |
Sandra B. Donaghy,
Joy Munk Smith |
source |
8 |
| SESUG |
2001 |
GETTING STARTED WITH PROC LOGISTIC |
Andrew H. Karp |
source |
5 |
| SCSUG |
2001 |
Evaluating the Use of Enterprise Guide in Introductory Statistics Classes |
Sandra B. Donaghy,
Joy Munk Smith |
|
8 |
| SCSUG |
2001 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
|
5 |
| SCSUG |
2001 |
Implementing Digital Analysis Using SAS |
Thomas J. Winn Jr. |
|
4 |
| SEUGI |
2001 |
A System for Monitoring and Analysing Legal Actions [presentation] |
Roberto Noceta |
source |
18 |
| SEUGI |
2001 |
Broadcasting Network WEB site Traffic Analysis [presentation] |
Donatella Gandino |
source |
37 |
| SEUGI |
2001 |
Customer Profiling System in Telecom Italia Mobile [presentation] |
Claudio Bocci,
Gianni Santerini |
source |
44 |
| SEUGI |
2001 |
Data Warehouse Implementation in Financial Statistics using SAS at State Statistical Office of Republic of Macedonia [presentation] |
Lidija Petkovska,
Valentina Jankovik |
source |
49 |
| SEUGI |
2001 |
Evolution of the Data Warehouse at the Russian Railways [presentation] |
Igor Movchikov |
source |
24 |
| SEUGI |
2001 |
Multi-objective modelling of decision making problems using SAS software [presentation] |
J. Pietrzykowski,
J. Granat,
P. Witan |
source |
30 |
| SEUGI |
2001 |
SAS Process Intelligence: Closing the "Knowing-Doing" Gap to Deliver Value Through Process Efficiency, Effectiveness and Adaptability [presentation] |
Ian D. Cox |
source |
38 |
| SEUGI |
2001 |
Simulation of risk values as a powerful tool of risk management optimization [presentation] |
C. Windolph,
E. Honak |
source |
19 |
| SEUGI |
2001 |
The Data Warhousing Process in the Development of Traffic Emission Information System of ATENA Project in Naples |
Giovanni Meccariello,
Livia Della Ragione,
Mario Rapone |
source |
12 |
| SEUGI |
2001 |
The Municipality of Venice Data Warehousing Project [presentation] |
Francesco Negrato |
source |
43 |
| PharmaSUG |
2001 |
Can standards be implemented effectively without compromising science? |
Amy Morris,
Blue Bell |
|
4 |
| PharmaSUG |
2001 |
FDA Reviewers as Ultimate End Users: Using the SAS System to Construct e-Submissions that Actually Facilitate the NDA / BLA Review Process |
Rich Vachal |
|
6 |
| PharmaSUG |
2001 |
Have You Ever Wished That You Do Not Need to Type or Change Report Numbers and Titles in Your SAS Programs? |
Aileen L. Yam |
|
6 |
| PharmaSUG |
2001 |
Unit-of-Analysis Programming |
Vanessa C. Hayden,
Fidelity Investments |
|
6 |
| SUGI |
2001 |
Clinical Trial System - A Front End SAS/AF Application |
Quan Ren |
source |
7 |
| SUGI |
2001 |
Data Modeling in Clinical Data Analysis Projects |
Gajanan Bhat |
source |
6 |
| SUGI |
2001 |
Efficient Statistical Programming? - Let SAS Do the Work |
Keiko I. Powers |
source |
4 |
| SUGI |
2001 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
source |
5 |
| SUGI |
2001 |
Outliers, Inliers, and Just Plain Liars - New Graphical EDA+ Techniques For Understanding Data |
Dave L. DesJardins |
source |
6 |
| SUGI |
2001 |
Preparing the SAS Software Programming Environment for Regulatory Submission |
Sunil Kumar Gupta |
source |
9 |
| SCSUG |
2000 |
Motorola's Engineering Data Analysis System: 10 Years of Analytical Excellence |
C. Michael Whitney,
Leslie Fowler |
|
7 |
| SESUG |
2000 |
Using the SAS System and QSR NUD*IST for qualitative data analysis (QDA) |
Robert G. Stewart |
source |
6 |
| NESUG |
2000 |
A Submission Development Environment to Support SAS Programming and Related Activities During Clinical Data Analysis |
Barry R. Cohen |
|
6 |
| WUSS |
2000 |
A Repeated Measurement of Analyzing the Qualities of Information from Different Web Sources |
Leping Liu,
George C. J. Fernandez |
source |
6 |
| WUSS |
2000 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
source |
5 |
| WUSS |
2000 |
How I Converted a Batch Application System to Client-Server and Lived to Tell About It |
Curtis A. Smith |
source |
8 |
| WUSS |
2000 |
Preparing the SAS Software Programming Environment for Regulatory Submission |
Sunil Kumar Gupta |
source |
5 |
| WUSS |
2000 |
SAS STAT applications in Econometrics |
Mathura Thillainathan,
George C. J. Fernandez |
source |
10 |
| SEUGI |
2000 |
An application of Image Editor and Image Management to recoreded traffic video images |
Giovanni Meccariello,
Livia Della Ragione,
Mario Rapone |
source |
9 |
| SEUGI |
2000 |
Business Intelligence in Telefonica I+D (R&D) [presentation] |
Alfredo Jesus Serrano |
source |
32 |
| SEUGI |
2000 |
Delfos: gas demand forecasting [presentation] |
Jose Manuel Galvez Canamaque |
source |
45 |
| SEUGI |
2000 |
Euro Blue Chips Index - A new benchmark for European Stock Markets [presentation] |
Emiliano Laruccia,
Marcello Esposito,
Stefania Carpi |
source |
33 |
| SEUGI |
2000 |
Finding the needle in a haystack: Fraud Detection on million records [presentation] |
Thierry Van de Merckt |
source |
28 |
| SEUGI |
2000 |
From Data Modeling to Business-to-Business Application Development: Targa Services/Fiat Auto Case [presentation] |
A. Dorigo,
A. Saccardi,
Giovanni Lux |
source |
28 |
| SEUGI |
2000 |
From ideas to technology - e-intelligence [presentation] |
Frank Johannsen |
source |
18 |
| SEUGI |
2000 |
Making Ends Meet - Using SAS to Develop the Electronic Record and Health Needs Assessment [presentation] |
Neil Serougi |
source |
15 |
| SEUGI |
2000 |
Managing IS costs through application performance management [presentation] |
Nicolas Lesage |
source |
18 |
| SEUGI |
2000 |
Mining in Melodies [presentation] |
Bulcsu Fajszi,
Laszlo Surjan |
source |
19 |
| SEUGI |
2000 |
Purchasing Budget & Price Evolution: tow innovative projects of Closed Loop implemented by the Liebert-Hiross group using the SAS System Technology [presentation] |
Andrea Provini,
Bruno Marelli,
Leonardo Flora |
source |
5 |
| SEUGI |
2000 |
SAS Data Warehouse for Risk Analysis in Vilniaus Bankas [presentation] |
Algirdas Laukaitis |
source |
41 |
| PharmaSUG |
2000 |
A Nonparametric Approach for the Statistical Analysis of Time to First Event in Censored Paired Data |
Roderick Lashley,
Dennis W. King,
Pam Marks |
|
3 |
| PharmaSUG |
2000 |
A SAS Tool for the Presentation and Statistical Analysis of Data from Bioavailability and Bioequivalence Studies |
Melvin S. Munsaka,
Carl R. Haske |
|
8 |
| PharmaSUG |
2000 |
A Submission Development Environment to Support SAS Programming and Related Activities During Clinical Data Analysis |
Barry R. Cohen |
|
6 |
| PharmaSUG |
2000 |
From Data to Study Report in One Step: A SAS Macro for the 2,2,2 Crossover Design |
Amy Morris,
Thomas E. Bradstreet |
|
5 |
| PharmaSUG |
2000 |
Reducing Statisticians' Programming Load: Automated Statistical Analysis with SAS and XML TM |
Michael C. Palmer |
|
5 |
| PharmaSUG |
2000 |
Using SAS for the Statistical Analysis of a Bivariate Primary Endpoint in a Clinical Trial of Chronic Fatigue Syndrome (CFS) |
Naum M. Khutoryansky,
David R. Strayer,
William A. Carter |
|
3 |
| SUGI |
2000 |
A Submission Development Environment to Support SAS Programming and Related Activities During Clinical Data Analysis |
Barry R. Cohen |
source |
6 |
| SUGI |
2000 |
An Extension to SAS/OR Software for Decision System Support |
Ali Emrouznejad |
source |
6 |
| SUGI |
2000 |
Dead Graphs - RIP (How Interactive Graphical EDA Techniques Markedly Enhance Data Analysis/Display) |
Dave L. DesJardins |
source |
9 |
| SUGI |
2000 |
Flexibility in Data Management Through the SAS System |
Shawn P. Thomas,
Brandon L. Welch,
Keely P. Casey |
source |
6 |
| SUGI |
2000 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
source |
5 |
| SUGI |
2000 |
How I Converted a Batch Application System to Client-Server and Lived to Tell About It |
Curtis A. Smith |
source |
|
| SUGI |
2000 |
Motorola's Engineering Data Analysis System: 10 Years of Analytical Excellence |
C. Michael Whitney,
Leslie Fowler |
source |
7 |
| SUGI |
2000 |
Preparing the SAS Software Programming Environment for Regulatory Submission |
Sunil Kumar Gupta |
source |
5 |
| SUGI |
2000 |
Warehousing, Metadata, and Object-Based Analysis |
Thomas H. Burger,
Philip M. Pochon |
source |
5 |
| SCSUG |
1999 |
Statistics Without DATA _NULLS_ |
Michael C. Palmer,
Cecilia A. Hale |
|
6 |
| SESUG |
1999 |
Statistics Without DATA _NULLS_ |
Michael C. Palmer,
Cecilia A. Hale |
source |
6 |
| WUSS |
1999 |
A Logistic Regression on the Qualities of Educational Research: Characteristics of Publishable Articles |
Leping Liu,
George C. J. Fernandez |
source |
5 |
| WUSS |
1999 |
Combining SAS Data Sets in Educational Research |
Leping Liu,
George C. J. Fernandez |
source |
6 |
| WUSS |
1999 |
Statistics Without DATA _NULLS_ |
Michael C. Palmer,
Cecilia A. Hale |
source |
6 |
| NESUG |
1999 |
Graphical Techniques for Displaying Multivariate Data |
James R. Schwenke,
Brian J. Fergen |
|
9 |
| NESUG |
1999 |
How New Graphical EDA Techniques Can Reveal Hidden Relationships Between the Criminal Behavior of Federal Prisoners and Their Thinking Patterns |
David DesJardins |
|
8 |
| NESUG |
1999 |
Visual Analysis on the WEB: Animating High Density Multidimensional Data |
Haftan M. Eckholdt |
|
9 |
| MWSUG |
1999 |
Sample Size Determination From A Pilot Bioequivalence Study For A Future Pivotal Bioequivalence Study: A SAS Procedure |
Xiang Gao,
Henry Cheng |
|
7 |
| SEUGI |
1999 |
Clinical processes and SAS/PH-Clinical, a good marriage? [presentation] |
Patrick Genyn |
source |
24 |
| SEUGI |
1999 |
Effective data warehousing - optimised MDDB in practice [presentation] |
Jacek Kaukiel |
source |
28 |
| SEUGI |
1999 |
Pharmaceutical application for stability (PASS) analysis |
Charles Stiffler,
Vesna Luzar-Stiffler |
source |
8 |
| SEUGI |
1999 |
SAS Applications in the exploring of life beginning data |
Jan Andrzej Domitrz,
Magdalena Topczewska |
source |
4 |
| SEUGI |
1999 |
Star's the limit.Ad hoc, cross-subject queries with the SAS system in a dimensional data warehouse [presentation] |
Wojciech Chybowski |
source |
30 |
| SEUGI |
1999 |
Supply chain management a new challenge for SAS data warehousing [presentation] |
Pascal de Poorter |
source |
33 |
| SEUGI |
1999 |
ThinProway-A Java client to a SAS application - A successful story. Exactly what you need? |
Riccardo Proni |
source |
9 |
| SEUGI |
1999 |
VELIX-Building the controlling and planning system concerning bonds, stocks futures and other securities for the DG Bank [presentation] |
Heinz-Peter Dickerman,
Jochen Kissel |
source |
31 |
| SUGI |
1999 |
An On-line Analytical System for Corrosion Pitting Analysis for Solid Rocket Booster with the SAS System |
Morgan C. Wang |
source |
5 |
| SUGI |
1999 |
Data Exploration Made Easy |
George C. J. Fernandez |
source |
7 |
| SUGI |
1999 |
How I Converted a Batch Application System to Client-Server and Lived to Tell About It |
Curtis A. Smith |
source |
5 |
| SUGI |
1999 |
How New Graphical EDA Techniques Can Reveal Hidden Relationships Between the Criminal Behavior of Federal Prisoners and Their Thinking Patterns |
Dave L. DesJardins,
Denise Golumbaski |
source |
6 |
| SUGI |
1999 |
Project RAPTOR: Implementation and Exploitation of a Manufacturing Data Warehouse |
Anne I. Brooks,
Roger Thompson |
source |
6 |
| SUGI |
1999 |
SAS/FSP Software: T ricking the Small Screen into Imitating Life |
Irene Mendelson |
source |
|
| SUGI |
1999 |
The Quality Data Warehouse - Solving Problems for the Enterprise |
Brad Klenz,
Donna O. Fulenwider |
source |
8 |
| SUGI |
1999 |
Three Methods to Produce Descriptive Statistics and Histogram Using SAS |
Bing Deng |
source |
4 |
| SUGI |
1999 |
Using SAS/INSIGHT Software as an Exploratory Data Mining Platform |
Robin Way |
source |
6 |
| SCSUG |
1998 |
JMP Reveals the Truth: Statistics Can Be Fun! |
William R. Gjertsen |
|
10 |
| WUSS |
1998 |
Data Warehouses and Bayesian Analysis - A Match Made by SAS |
Ram Gopalan |
source |
6 |
| WUSS |
1998 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
source |
5 |
| WUSS |
1998 |
How I Converted a Batch Application System to Client-Server and Lived to Write About It |
Curtis A. Smith |
source |
5 |
| WUSS |
1998 |
Multiple Regression and Model Selection on Developing a Computer Achievement Model |
Leping Liu,
George C. J. Fernandez |
source |
6 |
| WUSS |
1998 |
Quick Results from Statistical Analysis - An Alternative Approach to the Popular Menu Interface Systems |
George C. J. Fernandez |
source |
8 |
| NESUG |
1998 |
JMP Reveals the Truth: Statistics Can Be Fun! |
William R. Gjertsen |
|
12 |
| NESUG |
1998 |
SAS Makes Reproducing Easy |
Carolyn Kuntz |
|
6 |
| NESUG |
1998 |
Using a SAS/AF Frame Application to Unify and Simplify the Many Lubricant Tests in the ASTM TMC Lubricant Test Monitoring System |
Christine Bogdon |
|
7 |
| NESUG |
1998 |
Using SAS/IML to Calculate L-Moments for the Univariate Distribution Shape Parameters Skewness and Kurtosis |
Michael A. Walega |
|
8 |
| SESUG |
1998 |
Data Validation Using a SAS Format |
John R. Gerlach |
|
3 |
| SEUGI |
1998 |
A Data Warehouse Solution for Account Management |
Elena Battini |
source |
4 |
| SEUGI |
1998 |
Customer relationship management (CRM) research: How to spot, understand and respond to marketplace change signals |
Charles Stiffler,
Vesna Luzar-Stiffler |
source |
7 |
| SEUGI |
1998 |
Database marketing applications in the Italian banking sector |
Alberto Saccardi,
Guido Cuzzocrea |
source |
8 |
| SEUGI |
1998 |
Knowledge Discovery and Data Mining on the Example of Clinical Databases |
Leon Bobrowski,
Magdalena Topczewska |
source |
6 |
| SEUGI |
1998 |
The Implementation of a data warehouse at PTT Post International |
Tadek Miller |
source |
10 |
| SEUGI |
1998 |
Unpleasant data? A chance of powerful multi-variant analysis in clinical trials with data not meeting the conditions |
Thomas Bregenzer |
source |
13 |
| PharmaSUG |
1998 |
Integrating SAS and Adobe Acrobat into Electronic FDA Submissions |
Shylendra Kumar |
|
5 |
| PharmaSUG |
1998 |
Supporting the "Program-Analyze-Write-Review "Process with a Development Environment for Base SAS and the Macro Language |
Barry R. Cohen |
|
6 |
| SUGI |
1998 |
A Data Access Challenge: Build a SAS Frame Application for Access to an Informix Data Warehouse |
John E. Bentley |
source |
7 |
| SUGI |
1998 |
A Revolution in Data Analysis: How New, Very Powerful, Easy to Use, Graphical Data Analysis Tools and Techniques Can Empower Even Novice Subject Matter Specialists |
Dave L. DesJardins |
source |
8 |
| SUGI |
1998 |
Building the Framework for Enterprise Data Analysis in the Semiconductor Industry |
John T. Stokes,
Roger Thompson |
source |
6 |
| SUGI |
1998 |
Creating an ADP Center of Excellence: A Miltonian Approach of Looking Through Two Decades of "Visible Darkness" |
Peter Parker |
source |
6 |
| SUGI |
1998 |
Finding the Solution to Data Mining: A Map of the Features and Components of SAS Enterprise Miner Software Table of Contents |
John C. Brocklebank,
Mark Brown |
source |
24 |
| SUGI |
1998 |
PROC FACTOROR: A Tool for Extracting Hidden Gems from a Mountain of variables |
Jose A. Santos,
Lawrence Lippke,
Paul E. Pope |
source |
8 |
| SUGI |
1998 |
Supporting the "Program-Analyze-Write-Review "Process with a Development Environment for Base SAS and the Macro Language |
Barry R. Cohen |
source |
6 |
| SUGI |
1998 |
Using the Data Warehouse Model to Streamline and Accelerate New Drug and Medical Device Development |
Martin J. Rosenberg |
source |
5 |
| SCSUG |
1997 |
Reliability Data Analysis in the SAS System |
Gordon Johnston |
|
10 |
| PNWSUG |
1997 |
Use SAS/AF, SCL and MACRO to Build User-friendly Applications on UNIX |
Minghui Yang |
|
8 |
| PNWSUG |
1997 |
Using SAS/Insight as an Introductory Data Mining Platform |
Robin E. Way |
|
7 |
| WUSS |
1997 |
Economic Development and Women's Social Status: A SAS Analysis |
Seid M. Zekavat |
source |
7 |
| WUSS |
1997 |
Reliability Data Analysis in the SAS System |
Donna O. Fulenwider,
Gordon Johnson |
source |
10 |
| WUSS |
1997 |
The Use of Central Analysis File or Patient File in the Analysis and Management of Clinical Trials Data |
Ajit Gemunu de Silva |
source |
3 |
| WUSS |
1997 |
Using the Data Warehouse Model is Streamline and Accelerate New Drug and Medical Device Development |
Martin J. Rosenberg |
source |
5 |
| NESUG |
1997 |
CP-Nexus: A Clinical Data Warehouse at Columbia Presbyterian Medical Center |
Philip Burrowes |
|
4 |
| NESUG |
1997 |
Creating Column Delimited Files with Little or No Effort |
John Charles Gober |
|
7 |
| NESUG |
1997 |
Creating External Files Using SAS Software |
Clinton S. Rickards |
|
8 |
| NESUG |
1997 |
Evaluation of Client/Server Configurations for Analytic Processing |
Barry R. Cohen |
|
10 |
| NESUG |
1997 |
Graphically Enhancing Univariate Descriptive Statistics |
James R. O'Hearn |
|
3 |
| NESUG |
1997 |
SAS Versatility: Using SAS Software to Analyze and Report Students' Evaluations of Faculty |
Gail Wisan |
|
10 |
| MWSUG |
1997 |
New Evolving Roles in Research for Nurses Using SAS Development of an End-User Support System and Coordination of a Research Team |
Betty J. Anderson |
|
10 |
| MWSUG |
1997 |
Reliability Data Analysis in the SAS System |
Gordon Johnston |
|
10 |
| SESUG |
1997 |
Data Warehousing and Telemedicine |
James Zadinsky,
Fort Gordon |
|
5 |
| SESUG |
1997 |
Exploring Data With Base SAS Software |
Thomas J. Winn Jr. |
|
7 |
| SESUG |
1997 |
PROC FACTOR: How to Interpret the Output of a Real-World Example |
Rachel J. Goldberg |
|
8 |
| SEUGI |
1997 |
An application and visualization tool for the exploratory analysis of lifetime data |
Hans-Peter Altenburg,
Thomas Floren |
source |
6 |
| SEUGI |
1997 |
Analysing a bank's data using OLAP |
Eva Mièovská |
source |
12 |
| SEUGI |
1997 |
AWACS flight data - NATO surveillance, using a warehouse and graphics to visualise flight data |
Dario Nicolella,
G.P.W van Tol |
source |
12 |
| SEUGI |
1997 |
BMW (SA)-Where modelling for motoring is sensational with SAS! |
Lize-Marie Verhoef,
Ria Pretorius |
source |
17 |
| SEUGI |
1997 |
Do it yourself: tips and tricks in building your own application using SAS macro language |
Angelo Tinazzi |
source |
7 |
| SEUGI |
1997 |
Managing an insurance portfolio for profit and growth |
Harold Clarke,
Keith Chandler |
source |
19 |
| SEUGI |
1997 |
Object-oriented applications development at the Investment and Post Bank |
Jiøina Rokosovà |
source |
4 |
| SEUGI |
1997 |
The future of data warehousing |
Sean Kelly |
source |
28 |
| PharmaSUG |
1997 |
Visual Component Analysis: Interactive Graphical Modeling in SAS and ViSta/XLispStat |
Richard A. Faldowski |
|
13 |
| SUGI |
1997 |
DW + DM = $avings |
Robert J. Scharl,
Paul M. Centric |
source |
7 |
| SUGI |
1997 |
Effective Applications of Control Charts Using SAS Software |
Robert N. Rodriguez,
Sharad S. Prabhu |
source |
145 |
| SUGI |
1997 |
Evaluation of Client/Server Configurations for Analytic Processing |
Barry R. Cohen |
source |
10 |
| SUGI |
1997 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
source |
5 |
| SUGI |
1997 |
JMP Reveals the Truth: Statistics Can Be Fun! |
William R. Gjertsen |
source |
11 |
| SUGI |
1997 |
PROC FACTOR: How to Interpret the Output of a Real-World Example |
Rachel J. Goldberg |
source |
5 |
| SUGI |
1997 |
The Art and Science of Biostatistical Display |
Dominic T. Moore |
source |
4 |
| SCSUG |
1996 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
|
5 |
| SCSUG |
1996 |
Redesigning a Legacy: Techniques of a Quality Partner |
S. David Riba |
|
7 |
| SCSUG |
1996 |
Reponding to Change: Providing Data Warehouse Services as the Sources of the Data Evolve |
Kathe Richards |
|
7 |
| SCSUG |
1996 |
Why Knowing About Our Customers Helps Our Business |
Mark Brown |
|
4 |
| SESUG |
1996 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
|
5 |
| SESUG |
1996 |
Providing Data Analysis Support at a Major Research University using the SAS System |
Joy Munk Smith |
|
6 |
| SESUG |
1996 |
The Data Warehouse: Roles, Responsibilities, and Functions |
Christopher Toppe |
|
10 |
| NESUG |
1996 |
Macros Developed for Statistical Summary and Tabulation of Clinical Data |
William Sun,
David Lago,
David Handelsman,
Jack Shostak |
|
10 |
| NESUG |
1996 |
PROC FSVIEW: A Real Programmer's Tool |
Alan C. Wilson,
Marge Scerbo |
|
8 |
| NESUG |
1996 |
Statistical Analysis of Self-Organizing Maps |
Susan B. Garavaglia,
Asha Sharma |
|
10 |
| NESUG |
1996 |
The Role of SAS Programmers in Clinical Trial Data Analysis |
Ming Wang |
|
6 |
| MWSUG |
1996 |
Testing for and Correcting for Missing Data in Survey Responses: A Survey of Downtown Business in Minneapolis |
Shelly S. Baxter,
Lawrence C. Marsh |
|
10 |
| WUSS |
1996 |
ClinOS: A Commercially Available Set of Tools for SAS Programmers |
Lindley Frahm |
source |
8 |
| WUSS |
1996 |
Comparison of Different SAS Modules for Effective Data Analyses |
George C. J. Fernandez |
source |
2 |
| WUSS |
1996 |
Contrasts, Cell Means Model, and Missing Cells |
Joseph Campbell |
source |
4 |
| WUSS |
1996 |
Plots With Generalized Confidence Intervals Using SAS/GRAPH |
Linda C. Whitehand,
Bruce E. Mackey |
source |
5 |
| WUSS |
1996 |
Why Knowing About Our Customers Helps Our Business A Practical Application of Business Intelligence Software |
John McIntyre,
Marc Halsted |
source |
9 |
| SEUGI |
1996 |
Business geographics and Database Marketing with the SAS System |
Bengt Bengtsson |
source |
15 |
| SEUGI |
1996 |
Computational Changes in the Analysis of Data from Case-Control Studies |
Anette Pfahlberg,
Olaf Gefeller |
source |
9 |
| SEUGI |
1996 |
Graphical aspect of meta-analysis using SAS/GRAPH software and its specific annotate |
Angelo Tinazzi,
Fabrizio Carinci,
Valter Torri |
source |
15 |
| SEUGI |
1996 |
Intelligent query and reporting against DB2 |
Jens Dahl Mikkelsen |
source |
20 |
| SEUGI |
1996 |
Marketing Information System |
UNKNOWN |
source |
22 |
| SEUGI |
1996 |
PADRES: a system supporting the user friendly access and analysis of pharma Chemical Production Data |
B. Rutishauser,
H.W. Schrader,
Th. Graf |
source |
44 |
| SEUGI |
1996 |
Process Improvement Sudies in Appliance Manufacturing |
Hulya Yazici |
source |
6 |
| SEUGI |
1996 |
Product improvement data banks in SAS software - creation and utilisation |
A. Selmani,
F. Dorian |
source |
11 |
| SEUGI |
1996 |
Putting SAS/EIS software Viewers in Place for Multi-Dimensional Data Analysis |
Philip Mugglestone |
source |
26 |
| SUGI |
1996 |
A Statistical Analysis Macro Library in SAS Software |
Vivienne Ward,
Carl R. Haske |
source |
5 |
| SUGI |
1996 |
Choosing an Application Development Tool for Your CANDA |
Barry R. Cohen |
source |
8 |
| SUGI |
1996 |
Comparing Release 6.11 of the SAS System for Microsoft Windows 95 and Windows NT |
Mark W. Cates |
source |
10 |
| SUGI |
1996 |
Database Marketing and Business Geographies |
Mark Brown,
Jack Bulkley |
source |
6 |
| SUGI |
1996 |
Helping Nonstatisticians Visualize Quantitative Relationships: Using JMP Software's Unique Visualization Tools in the Business Environment |
Palmer Morrel-Samuels |
source |
3 |
| SUGI |
1996 |
RAD with SAS Software: Strategies, Techniques, and TipS |
Samuel Berestizhevsky,
Tanya Kolosova |
source |
6 |
| SUGI |
1996 |
SAS Software: One Stop Shopping for Re-engineering |
Diane E. Brown |
source |
5 |
| SUGI |
1996 |
SW-PQNG: A Life Cycle Model for Small Development Teams |
Roger K. Bolton |
source |
6 |
| SUGI |
1996 |
Teaching the SAS System as an Academic Subject |
Andrew H. Karp |
source |
|
| MWSUG |
1995 |
A Statistical Analysis Macro Library in SAS |
Carl R. Haske,
Vivienne Ward |
|
5 |
| MWSUG |
1995 |
PROACTIVE vs. REACTICE SPC Analysis at LTV Steel |
Paul M. Centric,
Robert J. Scharl |
|
6 |
| MWSUG |
1995 |
Randomization and Analysis of Body Weights in Rodent Toxicity Studies |
Jen-Fue Maa |
|
6 |
| NESUG |
1995 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
|
5 |
| NESUG |
1995 |
The Choice of SAS Software as the Application Development Tool for Your CANDA |
Barry R. Cohen |
|
9 |
| NESUG |
1995 |
Tired of Clincial SAS?: An Application for Drug Safety |
Jim M. Obritz,
Scott T. LaPorte |
|
4 |
| NESUG |
1995 |
Understanding Object Oriented Programming and the SAS/AF FRAME Entry |
Barry R. Cohen |
|
10 |
| SESUG |
1995 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
|
5 |
| SESUG |
1995 |
Information Visualization |
Ali Dogrusoz,
Nitin S. Patel,
Ronald E. Stogner |
|
4 |
| SEUGI |
1995 |
A Survival Analysis on Critical Components of Nuclear Power Plants |
Valerie Durbec |
source |
9 |
| SEUGI |
1995 |
Developing RADical SAS Applications |
Julian Ashworth |
source |
8 |
| SEUGI |
1995 |
Development of an Integrated SAS Based Drug Safety Information System at Geoden Richter |
Ferenc Sipos |
source |
4 |
| SEUGI |
1995 |
Development of the Decision Support System for the Executive Management at the Investment and Development Bank |
Ivan Slota |
source |
8 |
| SEUGI |
1995 |
Statistical Production Databases Using the SAS System |
Silvia Sima |
source |
14 |
| SEUGI |
1995 |
The SAS System for the Pharmaceutical Industry |
Patrick O'Dononghue |
source |
6 |
| SEUGI |
1995 |
The Times They are a Changing - The Increasing Case for a Multidisciplinary Approach to Statistical Applications |
Nicholas Graham Dyson |
source |
11 |
| SEUGI |
1995 |
UBIRIS - A System to Support Investment Research and Publications at UBS |
Beat Moser |
source |
10 |
| SUGI |
1995 |
Building a Client/Server EIS |
Greg Shanker,
David Hand |
source |
10 |
| SUGI |
1995 |
Conducting Linear Growth Curve Analysis with the SAS System |
Laura Ichikawa,
William E. Barlow |
source |
6 |
| SUGI |
1995 |
Getting Started with SAS/GRAPH the Easy Way |
Hany Aboutaleb,
Genevieve Kearse |
source |
7 |
| SUGI |
1995 |
Implementation of the FREOP System - The Quality Solution Provided for Northrop Grumman Corporation |
Donna O. Fulenwider,
Bradley W. Klenz,
Lorraine Schacht |
source |
6 |
| SUGI |
1995 |
Object-Oriented Programming with the SAS/AF FRAME Entry: CANDA Experiences |
Barry R. Cohen |
source |
9 |
| SUGI |
1995 |
Power Tools for Visualization of Information |
Ali Dogrusoz,
Nitin S. Patel,
Ronald E. Stogner |
source |
5 |
| SUGI |
1995 |
The Intricate Organization and Management of Clinical Research Laboratory Samples Using SAS/AF |
Jacqueline A. Wendel,
Daniel Nosek |
source |
6 |
| SUGI |
1995 |
Using SAS Macros to Develop a Quality Analysis Application System at China Steel Corporation |
Jin-Chyun Yang,
Jin-Shan Yang |
source |
8 |
| SCSUG |
1994 |
Exploring Data Using Base SAS Software |
Thomas J. Winn Jr. |
|
6 |
| SCSUG |
1994 |
Up to 50 x SAS Performance Gains on Large Data Volumes Using Scalable Parallel Computing |
Jesse Davis,
Helen Spade |
|
6 |
| WUSS |
1994 |
ROBOSAS: Laboratory Automation and SAS |
Charles R. Villarrubia,
Seth Michelson,
Ronald Rhodes,
Edward Leung |
source |
7 |
| WUSS |
1994 |
Up to 50 x SAS Performance Gains on Large Data Volumes Using Scalable Parallel Computing |
Jesse Davis,
Helen Spade |
source |
6 |
| NESUG |
1994 |
Exploratory Data Analysi When You Don't Have SAS/INSIGHT |
Michael A. Walega |
|
10 |
| NESUG |
1994 |
Migrating to SAS 6.08 for Windows: The Merck CANDA Experience |
Frank S. Palmieri,
Rob Rosen,
Wanda Bidlack |
|
7 |
| NESUG |
1994 |
Oject-Oriented Programming with the SAS/AF FRAME Entry: CANDA Experiences |
Barry R. Cohen |
|
9 |
| NESUG |
1994 |
Preliminary Data Management and Report Generation Using the SAS System on the PC |
Carmen F. Gillern,
William C. Murphy,
Ronald J. Billings |
|
3 |
| MWSUG |
1994 |
Facilitating Continuous Quality Improvement with SAS/ASSIST Software |
Priscilla Van Grevenhof,
Rita Black,
Jo Johnson,
Cynthia Libson |
|
5 |
| MWSUG |
1994 |
SAS: The Complete Solution for Medical Data Analysis |
Diane E. Brown |
|
10 |
| SESUG |
1994 |
Critical Steps to Meaningful Causal Data Analysis |
Deborah Wall |
|
4 |
| SESUG |
1994 |
Up to 50 x SAS Performance Gains on Large Data Volumes Using Scalable Parallel Computing |
Jesse Davis,
Helen Spade |
|
6 |
| SEUGI |
1994 |
A Unique Application Generator for the Management and Control of Clinical Trials Data |
Chaim Singal |
source |
9 |
| SEUGI |
1994 |
Aiming at More Efficient System Support for the R&D Process |
Mark Crawford,
Winfried Koch |
source |
8 |
| SEUGI |
1994 |
An Introduction to the Automatic Reporting Environment of PMS Norden |
Hilde Anita Larsen |
source |
7 |
| SEUGI |
1994 |
Analysis of Dose-response Curves in Molecular Pharmacology by the SAS System |
Paola Baiardi |
source |
10 |
| SEUGI |
1994 |
ATMOSFERA a Computer System Developed with SAS Software for Management, Forcasting and Analysis of Metereological Data and Atmospheric Pollution in Urban Territory Data |
P. Fedelel,
G. Grandoni,
M. C. Mammarella,
G. Marcon,
M. Sanarico |
source |
11 |
| SEUGI |
1994 |
Model-Independent Pharmacokinetics Using SAS/PH-Kinetics Software |
Brian Fredric |
source |
5 |
| SEUGI |
1994 |
Neural Networks and Statistical Models |
Derek Powell,
Martin Duffy |
source |
9 |
| SEUGI |
1994 |
Project Planning and Control System |
Arturo Busso,
Jakob Weinstock,
Mercedes Lifsitz |
source |
8 |
| SEUGI |
1994 |
Rapid Applications Development to Assure Critical Success Through Quality |
Ian D. Cox |
source |
10 |
| SEUGI |
1994 |
Starting with the SAS System in the Central Bureau of Statistics in Croatia |
Srdan Dumicic,
Zrinka Marusic |
source |
7 |
| SEUGI |
1994 |
The Analysis of Data from Case-control Studies Which Statistical Methods and Software Products are Used |
Olaf Gefeller |
source |
9 |
| SEUGI |
1994 |
The ASSIST System |
Martin McGill |
source |
2 |
| SEUGI |
1994 |
We Must Achieve an Intergrated Approach to the Presentation of Systems if we are ever to Realise the Full Benefit of "Open Systems" [presentation] |
David Hand |
source |
7 |
| SUGI |
1994 |
Consulting Questions: Should I Become a Consultant? Which Consultant Should I Hire? |
Deb Cassidy |
source |
6 |
| SUGI |
1994 |
Converting Mainframe Technical Information Resources to a Distributed Environment Using SAS: Two Case Studies |
Kalman J. Gyirnesi,
Gregg A. Spindler,
Richard A. DeVenezia |
source |
5 |
| SUGI |
1994 |
Exploring Data With Base SAS Software |
Thomas J. Winn Jr. |
source |
6 |
| SUGI |
1994 |
Interactive Data Management and Analysis Using JMP Software, SAS Software, and OpenVMS in a Networked User-Friendly Environment |
David N. Ikle,
William F. Kastner |
source |
5 |
| SUGI |
1994 |
Migrating to SAS 6.08 for Windows: The Merck CANDA Experience |
Frank S. Palmieri,
Rob Rosen,
Wanda Bidlack |
source |
6 |
| SUGI |
1994 |
Neural Network Implementation in SAS Software |
Warren S. Sarle |
source |
23 |
| SUGI |
1994 |
Neural Networks and Statistical Models |
Warren S. Sarle |
source |
13 |
| SUGI |
1994 |
Preliminary Data Management and Report Generation Using the SAS System on the PC |
Carmen F. Gillem,
William C. Murphy,
Ronald J. Billings |
source |
3 |
| SUGI |
1994 |
Replacement Methodology or Maintaining the Ranking of Treatments in Clinical Trials with Discontinuations |
Maureen Fulcher Mele |
source |
6 |
| SUGI |
1994 |
Scientific Visualization in Oil and Gas Exploration |
Leon L. Fedenczuk,
Brian Wyvill,
Kristina Hoffmann |
source |
6 |
| SUGI |
1994 |
Using SAS Software to Simulate Questionnaire Style Data |
John F. Walsh |
source |
2 |
| NESUG |
1993 |
Improving Service Industry Quality with the SAS System |
Katherine J. Roggenkamp,
Robert N. Rodriguez |
|
1 |
| NESUG |
1993 |
Reading SPC Data in SAS from other Applications |
Prabhakar Jain |
|
8 |
| NESUG |
1993 |
Use of PROC IML to Calculate L-Moments for the Univariate Distributional Shape Parameters Skewness and Kurtosis |
Michael A. Walega |
|
8 |
| WUSS |
1993 |
Improving Service Quality With the SAS System |
Robert N. Rodriguez,
Katherine J. Roggenkamp |
source |
2 |
| SCSUG |
1993 |
Exploring Data Using Base SAS Software |
Thomas J. Winn Jr. |
|
30 |
| MWSUG |
1993 |
Analysis of Incomplete Categorical Repeated Measures |
Charles S. Davis |
|
6 |
| MWSUG |
1993 |
Data Ansalysis Semicolon-Free: Using SAS without the Syntax |
Julia Brooks |
|
3 |
| MWSUG |
1993 |
Data Integrity Validation - Proactive vs. Reactive |
Douglas P. DeYoung |
|
6 |
| MWSUG |
1993 |
Learning SAS by Diagrams and Examples |
Joanne Peng,
Shu-Yeng Wong |
|
7 |
| SEUGI |
1993 |
A Bayesian Analysis for Panel Based Data |
Roger Owen |
source |
11 |
| SEUGI |
1993 |
An Information Systems Breakthrough at Tesco |
Ian Stimson |
source |
5 |
| SEUGI |
1993 |
Data Visualisation with SAS/INSIGHT Software |
Gerhard Held |
source |
10 |
| SEUGI |
1993 |
Exploratory Data Analysis Using SAS Software |
Gerhard Held |
source |
11 |
| SEUGI |
1993 |
Producing Training Materials in Support of SAS Software Using SAS/AF Software |
Ian Cantley |
source |
15 |
| SEUGI |
1993 |
The SAS System - Strategic Software for the Future in the Hungarian Central Statistical Office |
Eva Papp |
source |
5 |
| SEUGI |
1993 |
User Experience in Designing and Implementing a CICS Performance Monitoring Application Using the SAS System |
Ercument Ulguner |
source |
17 |
| SEUGI |
1993 |
Variable Selection Techniques Implemented in Procedures of SAS Software |
Olaf Gefeller |
source |
9 |
| SUGI |
1993 |
A Generalized SAS Management System for Online Data Entry Applications |
Roger Mueller,
Priscilla E. Van Grevenhof |
source |
6 |
| SUGI |
1993 |
A Simulation-Based Project For Experimental Design Based on SAS Software |
Michael Friendly |
source |
8 |
| SUGI |
1993 |
Administering a Large, Long-Term Clinical Trial Requiring a Hierarchical Database Using the SAS System, Release 6.07 |
Mitchell Snyder,
Mark Goldberg,
Michal Benderly |
source |
6 |
| SUGI |
1993 |
Double-Key Data Entry/Verification in SAS Software: Part of Downsizing a Clinical Data System to the OS/2 Operating System |
Barry R. Cohen |
source |
7 |
| SUGI |
1993 |
Exploratory Data Analysis Using SAS Software |
Greg J. Weier,
Randall D. Tobias |
source |
11 |
| SUGI |
1993 |
Guided Data Analysis with SAS/LAB Software |
Katherine J. Roggenkamp,
Wayne E. Watson,
Randall D. Tobias |
source |
7 |
| SUGI |
1993 |
Learning SAS by Diagrams and Examples |
Chao-Ying Joanne Peng,
Shu-Yeng Wong |
source |
6 |
| SUGI |
1993 |
Re-engineering the Drug Development Process with 'the SAS Information Delivery System |
Bryan K. Beverly |
source |
5 |
| SUGI |
1993 |
SAS/LAB Software for Guided Data Analysis |
Wayne E. Watson,
Katherine J. Roggenkamp,
Randall D. Tobias |
source |
7 |
| SUGI |
1993 |
SAS/PH-Clinical Software: CANDA Implementation Strategies |
Juliana M. Ma,
Sandra D. Schlotzhauer |
source |
8 |
| SUGI |
1993 |
STAB: A PC/SAS Stability Analysis Software |
Moh-Jee C. Ng,
Yi Tsong |
source |
8 |
| SUGI |
1993 |
Structured Systems Engineering and the SAS System: Godzilla Versus Megalon |
James E. Johnstone,
Stuart Leven |
source |
10 |
| SUGI |
1993 |
System Trending for Statistical Analysis of System Performance Measurement of Plant Wellness |
Joseph G. Moyer,
Steve Leshnoff,
Mark Orski,
Judy Keiper |
source |
6 |
| SUGI |
1993 |
The Progression and Integration of the CANDA at Merck |
Bruce Binkowitz,
Wanda Bidlack,
Nancy Bauer |
source |
6 |
| SUGI |
1993 |
The SAS System in a Longitudinal Environmental Health Intervention Study with Repeated Monitoring |
WinKey Pan |
source |
4 |
| SUGI |
1993 |
Universal Data Access: A Success Story |
Bruce Babbitt,
Marianna Suciu,
Emily P. Wallace |
source |
5 |
| SUGI |
1993 |
Using the SAS ADX Menu System for Continuous Quality Improvement |
Melissa A. Durfee |
source |
6 |
| SESUG |
1993 |
Statistical Analysis of Cardiac Electric Vectors Using SAS |
C. Doiron,
G. W. Morrison,
D. G. BaIl,
R. D. Graves |
|
5 |
| NESUG |
1992 |
Getting to Know Your Data Using SAS |
Felicia Borglum |
|
7 |
| NESUG |
1992 |
Introduction to Release 6.08 SAS/INSIGHT and SAS/LAB Software |
Mark Brown |
|
6 |
| MWSUG |
1992 |
Introduction to Release 6.08 SAS/INSIGHT and SAS/LAB Software |
Mark Brown,
Marshall P. Scott |
|
6 |
| MWSUG |
1992 |
Marketing Research: Uncovering Competitive Advantages |
Warren F. Kuhfeld |
|
9 |
| MWSUG |
1992 |
Using SAS Macro Facilities to Simplify A Large Multi-Event Statistical Analysis |
Douglas P. DeYoung |
|
6 |
| MWSUG |
1992 |
Using SAS to Maintain Historical Databases of Research Project Information |
Susanne L. Daood,
Randy Stick |
|
7 |
| SEUGI |
1992 |
Analysing Business and Economic Data with SAS/ETS Software |
Georg Morsing |
source |
9 |
| SEUGI |
1992 |
Basic Problems of Analysing Disease Data in Epidemiologic Applications |
Anette Pfahlberg |
source |
7 |
| SEUGI |
1992 |
Guided Data Analysis with SAS/LAB Software |
Gerhard Held |
source |
7 |
| SEUGI |
1992 |
Improve Speed and Quality in Clinical Trial Analysis Using SAS Macros |
Mark de Somer |
source |
12 |
| SEUGI |
1992 |
Interface of the SAS System by YAFOOL |
Media Mhiri |
source |
11 |
| SEUGI |
1992 |
Marketing Research - Uncovering Competitive Advantage |
Gerhard Held |
source |
8 |
| SEUGI |
1992 |
Writing a 4 GL for Statistical Analysis of Customised Databases |
Eoin O'Brien,
Neil Atkins |
source |
9 |
| SUGI |
1992 |
Analysis of Incomplete Categorical Repeated Measures |
Charles S. Davis |
source |
6 |
| SUGI |
1992 |
Analyzing Business and Economics Data with SAS/ETS Software |
Mark Little |
source |
9 |
| SUGI |
1992 |
Interactive Data Analysis Strategies |
Alvin M. Best III |
source |
6 |
| SUGI |
1992 |
Load Data Analysis Workstation (LDAW): A SAS/AF Information Systems Application |
Burtt Blodgett,
John Powers |
source |
6 |
| SUGI |
1992 |
Marketing Research: Uncovering Competitive Advantages |
Warren F. Kuhfeld |
source |
9 |
| SUGI |
1992 |
Pharmacokinetic Statistical Analysis System - A SAS/AF and SAS/FSP Application |
Sharon Passe,
Andrea L. Contino |
source |
6 |
| SUGI |
1992 |
Running the Business: Financial Management with the SAS System |
Jeff Babcock |
source |
14 |
| SUGI |
1992 |
SAS Software - The Power Tool for Information Professionals |
Shane Wood |
source |
5 |
| SUGI |
1992 |
Some Considerations in Designing SAS-Based Data Management Systems for Large International Epidemiologic Studies |
Cynthia L. Johnson,
Michael Arrighi,
Priscilla E. Van Grevenhof,
Roger Mueller,
Laurel Panser,
Robert Lee,
C. Chute |
source |
9 |
| SUGI |
1992 |
Using SAS Software to Teach a University Course in Statistical Computing and Database Management |
John L. Wasik |
source |
6 |
| SUGI |
1992 |
Using SAS/Access Software and Database Management Systems in a Distributed Environment |
Jana Van Wyk |
source |
10 |
| SUGI |
1992 |
Using the SAS System for Medical Data Processing and Event Analysis: An Overview |
Harald Pitz,
Marcus Frenz,
Hans-Peter Howaldt |
source |
6 |
| NESUG |
1991 |
PIAF-A Real End-User Computing Environment |
Paul Proulx,
Nancy Faille |
|
6 |
| MWSUG |
1991 |
A Comparison of RS/I and SAS Software in Meeting Information System Development Needs |
Michael S. Lajiness |
|
7 |
| MWSUG |
1991 |
Computer Performance Evaluation for UNIX |
Robert K. Newman |
|
6 |
| SEUGI |
1991 |
An Interface to the SAS System by Yafool |
Ali Mili,
Hedia Mhiri Sellami,
Roland Ducournaw |
source |
9 |
| SEUGI |
1991 |
An International Forestry Information Delivery System |
Felice Padovani |
source |
10 |
| SEUGI |
1991 |
Confidence Intervals for Bioequivalence Studies |
B. Jones,
D. J. Nichols,
P. Blood |
source |
12 |
| SEUGI |
1991 |
Current Status of the SAS System in the Soviet Union |
Harry Bush |
source |
7 |
| SEUGI |
1991 |
Data-Analysis with SAS/GRAPH Software |
H.C.M. van der Knaap |
source |
10 |
| SEUGI |
1991 |
Features of SAS/PH-Clinical Software |
Gerhard Held,
Patrick O'Donoghue |
source |
10 |
| SEUGI |
1991 |
Implementation of the SAS System in the Danish Fur Breeders Association |
Ejner Børsting,
Jesper Clausen |
source |
4 |
| SEUGI |
1991 |
Inferences Control in Data Bases |
A. Bekhechi |
source |
8 |
| SEUGI |
1991 |
Interpretation-Driven Analysis Using SAS/LAB Software |
Randall D. Tobias |
source |
7 |
| SEUGI |
1991 |
STARS: Statistical and Reporting System for Clinical Research Data |
A. Longoni,
G. Marcon,
M. Sanarico,
R. Ferrara |
source |
7 |
| SEUGI |
1991 |
Statistical Evaluation and Forecasting of Steel Corrosion Data |
Bernhard Kienzler,
Emanuel Smailos,
Rainer Koester |
source |
11 |
| SEUGI |
1991 |
Why SAS Software for OPCS |
Richard Somerville |
source |
5 |
| SUGI |
1991 |
A Comparison of RS/1 and SAS Software in Meeting Information Systems Development Needs .. . |
Loren L. Heun,
Michael S. Lajiness |
source |
8 |
| SUGI |
1991 |
Customized In-House Training with a SAS Trainer's Kit |
Marcia S. Murto |
source |
3 |
| SUGI |
1991 |
Features of SAS/PH-Clinical Software |
Sandra D. Schlotzhauer |
source |
10 |
| SUGI |
1991 |
How Good is Your Data: A Discussion of the Measurement Process |
Annabeth L. Propst |
source |
3 |
| SUGI |
1991 |
Ridge Regression from Correlation Matrix Input |
Lawrence Hotchkiss,
John R. Gerlach |
source |
6 |
| SUGI |
1991 |
Taking a Bite Out of SAS Software: Jaw Motion Studies on a PC |
William C. Murphy,
Howard M. Proskin,
Ross H. Tallents |
source |
4 |
| SUGI |
1991 |
Texas Instruments' Workstation Interface for Statistical Analysis and Reporting of Data (WISARD) |
Jim Wyatt |
source |
4 |
| SUGI |
1991 |
The TPSTAT System for the Analysis and Reporting of Toxicology and Pathology Data and Its Implementation under Version 6 of the SAS Software |
Murray R. Selwyn,
Peter P. Gaccione,
Scott E. Moseley,
Virginia M. Ashe |
source |
6 |
| SUGI |
1991 |
The Use of the SAS System in Statistical Training |
William L. Sanders |
source |
4 |
| SUGI |
1991 |
Using the Power of SAS Software to Manage a Graphical Database |
Rich Priem,
Anita Clark |
source |
6 |
| NESUG |
1990 |
Developing a SAS/AF System for Statistical Process Control (SPC) Applications |
Melissa A. Durfee |
|
6 |
| NESUG |
1990 |
Understanding PROC UNIVARIATE Statistics |
Wendell F. Refior |
|
5 |
| NESUG |
1990 |
Using SAS/ASSIST Software to Develop End-User |
John McIntyre |
|
5 |
| SEUGI |
1990 |
A SAS System for Timesheet Processing |
Hugh O'Neill,
Kathryn Pocock |
source |
10 |
| SEUGI |
1990 |
Directions of the SAS System in Statistics and Decision Support |
Gerhard Held |
source |
7 |
| SEUGI |
1990 |
Multivariate Outlier Detection |
Christian Derquenne |
source |
9 |
| SEUGI |
1990 |
Robust Estimation of Radio Immuno Assays Using SAS Software |
Hans-Peter Altenburg |
source |
8 |
| SEUGI |
1990 |
SAS/ASSIST Software: A Programmer's View |
Jan Bakker,
Philip J. Winters |
source |
7 |
| SEUGI |
1990 |
SAS/INSIGHT Software Data Visualisation with the SAS System |
Gerhard Held,
Thomas J. R. Emmerich |
source |
10 |
| SEUGI |
1990 |
Training Curriculum for Release 6.06 and Beyond |
Karl Hoffman |
source |
5 |
| SUGI |
1990 |
An Exploratory Data Analysis Approach to Qualitative Response Modeling Using SAS/IML and SAS/GRAPH Software |
Merwyn L. Elliott,
Ross Hightower,
Caleb Chan |
source |
6 |
| SUGI |
1990 |
Aspects of LAN-Based Decision Support Systems |
Eric M. Klusman |
source |
4 |
| SUGI |
1990 |
Constructing Integrated Clinical Information Systems for Traditional and Nontraditional Users |
Martin J. Rosenberg |
source |
6 |
| SUGI |
1990 |
Developing Release 6.03 SAS/AF Applications as a Statistical Teaching Aid |
L. M. Harschnitz,
Laurie A. Abell |
source |
6 |
| SUGI |
1990 |
Estimation of Area Under Concentration - Time Curves (AUC) Using the LAG Function and the Trapezoidal Rule |
R. A. Rogers,
W. L. Tippitt |
source |
1 |
| SUGI |
1990 |
Management Reporting for Capacity Planning and Computer Performance Evaluation |
Donald T. Gantz |
source |
12 |
| SUGI |
1990 |
Menuing Through the SAS System: Version 6 |
Kirk Paul Lafler |
source |
9 |
| SUGI |
1990 |
Mortar and Bricks: Using Basic SAS System Procedures to Manipulate Your Data |
Peter Kretzman |
source |
8 |
| SUGI |
1990 |
Using the ADX Menu System for Taguchi Applications in Quality Improvement |
Randall D. Tobias |
source |
15 |
| NESUG |
1989 |
A Trauma Registry System Using the SAS System and dBASE III Plus |
Andrew Greenleaf,
Sivaram Kalyandrug |
|
8 |
| NESUG |
1989 |
Integrated Clinical Information Systems for Traditional and Non-traditional Users |
Martin J. Rosenberg |
|
8 |
| NESUG |
1989 |
Modular Course Design |
Kim Burch |
|
7 |
| NESUG |
1989 |
Supporting SAS Users in a University: Where is the Future ? |
Jean Hardy |
|
4 |
| SEUGI |
1989 |
Introducing A New Statistical Package (i,e. SAS Software) In A University Environment |
Per H. Jacobsen |
source |
10 |
| SUGI |
1989 |
A Data Management System for Remote Medical Studies Using the SAS System |
Timothy L. Cannon,
Gene O. Nelson,
Dwayne D. Oland,
David M. Warren |
source |
3 |
| SUGI |
1989 |
A System of SAS Macros to Produce Kaplan-Meier Life Tables, Plots, and Stratified Mantel-Haenszel Comparisons |
James M. Boyett,
Kirk A. Easley |
source |
6 |
| SUGI |
1989 |
An Integrated Approach to Computer Systems for NDA Preparation and Presentation |
Martin J. Rosenberg |
source |
7 |
| SUGI |
1989 |
Analyzing Space-Use Data with a Harmonic Mean Estimator in the SAS System |
Larry J. Layne,
Paul F. Steblein |
source |
5 |
| SUGI |
1989 |
Building a Scientific Computing Environment Using the SAS System |
Jody J. Fromer |
source |
2 |
| SUGI |
1989 |
But Will it Sell? Market-based Decision Systems Using SAS Software |
Lee H. Evans |
source |
9 |
| SUGI |
1989 |
Determining the Roles of the SAS System and a Database Management System in Clinical Research |
Mark J. Holdbrook |
source |
5 |
| SUGI |
1989 |
Improving Program Efficiency through Coding Techniques |
Daniel E. Lodter |
source |
6 |
| SUGI |
1989 |
Most Creative Use of the Software-Monochrome |
Leslie Worf |
source |
116 |
| SUGI |
1989 |
Multivariate Models for the Analysis of Crossover Experiments |
Vernon M. Chinchilli,
Ronald K. Elswick |
source |
5 |
| SUGI |
1989 |
PC TIMS: A SAS Software Integrated System for Technical Information Management |
Anthony B. Kreamer,
Ronald R. MacDonald,
Stephen J. Medvid,
Shi-Tao Yeh |
source |
7 |
| SUGI |
1989 |
SAS Software and IBM Corporation's DB2: An End User Computing Strategy |
Thomas A. Miron |
source |
4 |
| SUGI |
1989 |
SAS/ASSIST' Software: Bringing the Power of the SAS System to the User |
Brenda Erickson,
Tammy L. Gagliano,
Gail Kramer,
Katherine J. Roggenkamp |
source |
6 |
| SEUGI |
1988 |
A Procedure for Documenting and Assessing Bioequivalence |
Alfredo Ardia,
C. Montoro,
N. Orlando |
source |
11 |
| SEUGI |
1988 |
Automatic Analysis of Clinical Trials |
J. C. Peyrieux |
source |
6 |
| SEUGI |
1988 |
New Developments in Psychometric and Market Research Procedures |
Gerhard Held |
source |
5 |
| SEUGI |
1988 |
PETBASE, A Statistical Data Base System for the Anatomically Based Analysis of PET DATA |
Curt Beil,
H. Bonner,
U. Pietrzyk |
source |
11 |
| SEUGI |
1988 |
SAS/GRAPH Software and Spatial Analysis |
Danilo Bofigli |
source |
13 |
| SEUGI |
1988 |
The Role of the SAS System within the Software Base of a Scientific Community |
Mark Venn,
Nick Teall |
source |
7 |
| SUGI |
1988 |
A GPSS-like Language in the SAS System for Discrete-Event Simulation |
Michael A. Greene,
Gretchen K. Jones |
source |
5 |
| SUGI |
1988 |
A Statistical Analysis of the Zip+4 Data Base |
Peter Weiss |
source |
6 |
| SUGI |
1988 |
An Intelligent Interface to the SAS System for Use by Product Development Engineers |
Debra D. Spencer |
source |
6 |
| SUGI |
1988 |
CADAE: Computer-assisted Design and Analysis of Response Surface Experiments |
Mark J. Levine |
source |
4 |
| SUGI |
1988 |
Color Hard Copy Technology-Plotters and Printers |
Daniel Lee |
source |
5 |
| SUGI |
1988 |
Helping Naive Users: An Expert System to Prepare Initial SAS Analysis |
David King,
Shoko Tsuji,
Laurie Zant |
source |
4 |
| SUGI |
1988 |
New Developments in Pyschometric and Market Research Procedures |
Warren F. Kuhfeld,
Forrest W. Young |
source |
5 |
| SUGI |
1988 |
PBS: An Intelligent Statistical System for Laboratory Scientists |
Stan Altan,
Thomas F. Devlin |
source |
3 |
| SUGI |
1988 |
The Application of the SAS Macro and Autocall Facilities to a Customized Exploratory Data Analyzing System |
Marc Alary,
William A. R. Orban |
source |
3 |
| SUGI |
1988 |
The Selling of SAS Software: Toward a Unified Analysis Environment in Basic Research |
Mark H. Bradshaw |
source |
2 |
| SUGI |
1988 |
Use of the SAS System in an Undergraduate Course on Statistical Packages at the University of Central Florida |
Thian S. Kheoh,
Dale F. Kraemer,
Julie Wildman-Pepe |
source |
3 |
| SUGI |
1988 |
User Surveys: The Key to Customer Satisfaction and Happiness |
Sandra Robinson,
Sallie R. Teaf |
source |
5 |
| SUGI |
1988 |
Using the SAS System to Facilitate Clinical Trials Research and NDA Approval |
Martin J. Rosenberg |
source |
7 |
| SEUGI |
1987 |
A General Application for the Optimisation of Data Analysis |
Gerhard Hugues |
source |
5 |
| SEUGI |
1987 |
A Statistical Look at Risk Factors for Coronary Heart Disease |
David J. Shannon |
source |
15 |
| SEUGI |
1987 |
Effective Use of SAS Software In a Large-Scale Sample Survey |
Risto Lehtonen |
source |
15 |
| SEUGI |
1987 |
Visual Explanatory Data Analysis |
Forrest W. Young |
source |
11 |
| SUGI |
1987 |
A Laboratory Notebook in SAS Software |
Caroline M. Bobik,
Arthur C. Singer |
source |
8 |
| SUGI |
1987 |
An Example of an Integrated Programming and Data Analysis System |
Eric M. Klusman |
source |
8 |
| SUGI |
1987 |
Establishing a SAS Consulting Service at a Large Research University |
Ronald Kalinoski,
John Podgurski |
source |
6 |
| SUGI |
1987 |
High-Performance Graphics for Exploring Multivariate Data |
Harold W. Gugel,
C. Ming Wang |
source |
8 |
| SUGI |
1987 |
Using SAS Software to Develop a Prototype for Determining Participant Profiles and for Assessing Potential Relationships Among Health Insurance Variables |
Ralph F. Catalanello,
Bruce W. Eagle |
source |
6 |
| SUGI |
1987 |
VISUALS: Experimental Software for Dynamic Hyperdimensional Graphics |
Douglas P. Kent,
Warren F. Kuhfeld,
Forrest W. Young |
source |
10 |
| SEUGI |
1986 |
A SAS Installation's Critics |
Roland E. Forster |
source |
6 |
| SUGI |
1986 |
A Simplistic Approach to Tabulating and Summarizing Clinical Laboratory Data |
Carol A. Bogardus,
Les Pennelly |
source |
3 |
| SUGI |
1986 |
A System for the Analysis of Cohort Mortality Data |
Edward L. Frome,
Richard W. McLain |
source |
3 |
| SUGI |
1986 |
An Integrated Approach to Clinical Data Entry &Management Using Personal Computers and SAS Software |
Robert W. Heinemeyer |
source |
6 |
| SUGI |
1986 |
Power Analysis for Linear Models |
Ralph G. O'Brien |
source |
8 |
| SUGI |
1986 |
The SAS System in Litigation Support |
Bernard Yancey |
source |
8 |
| SUGI |
1986 |
Using the SAS System to Perform Power Analyses for Log-Linear Models |
Ralph G. O'Brien |
source |
7 |
| SUGI |
1986 |
Visual Exploratory Data Analysis: PROC VISUALS, A User-Written Experimental SAS Procedure |
Thomas C. Edds,
Douglas P. Kent,
Warren F. Kuhfeld,
Forrest W. Young |
source |
6 |
| SEUGI |
1985 |
A User-Friendly Application System Based on the SAS System |
Franz Lasinger |
source |
8 |
| SEUGI |
1985 |
Data Analysis and the Information Centre |
Aale Roos |
source |
5 |
| SUGI |
1985 |
Development of Graphical Tools for Enhancements to SAS/GRAPH Software |
Kikuo Nakazawa,
Hiroshi Takaya,
Michiya Tomita,
Masafumi Yoshida |
source |
6 |
| SUGI |
1985 |
Enhancing Printout of SAS Data Sets Using Macros |
Gary Vair |
source |
6 |
| SUGI |
1985 |
Help SAS System Users with an RBBS |
P. L. Olympia |
source |
4 |
| SUGI |
1985 |
Macros for Paired Categorical or Continuous Scale Data Analysis |
Thomas E. Bradstreet |
source |
8 |
| SUGI |
1985 |
New Developments in Describing and Visualizing Multivariate Data |
Forrest W. Young |
source |
9 |
| SUGI |
1985 |
Statistical Graphics Made Possible by the SAS/GRAPH ANNOTATE Facility under VMS |
Patricia M.D. Benoit |
source |
7 |
| SUGI |
1985 |
Suitability of Microcomputers for Statistical Analysis |
Phil Spector |
source |
4 |
| SUGI |
1985 |
Taking Advantage of the Mapping and Three-dimensional Display Capabilities of SAS/GRAPH Software |
Bradford S. Simmons |
source |
4 |
| SUGI |
1985 |
The Introduction of SAS Software and the Strategy Used to Spread Its Use |
Akira Yagi |
source |
6 |
| SUGI |
1985 |
The Obsolescence of the SAS System |
Grant Blank |
source |
6 |
| SUGI |
1985 |
The SAS System as a Statistical Simulation Language |
Timothy J. Breen,
Robert M. Hamer |
source |
8 |
| SUGI |
1985 |
Writing SAS Procedures |
Terri L. Betancourt |
source |
7 |
| SEUGI |
1984 |
A Statistical Analysis of CPU Overhead Factors |
Alan J. Knight,
Richard Alexander |
source |
24 |
| SEUGI |
1984 |
A Workload Analysis and Forecasting Study |
Carlo Grandi |
source |
25 |
| SEUGI |
1984 |
New Statistical Features in SAS |
Gerhard Held |
source |
13 |
| SEUGI |
1984 |
SYSPAD French Methods of Data Analysis |
Bernard Piot,
J. M. Bouroche,
Stephane Corre |
source |
7 |
| SEUGI |
1984 |
Working with SAS in a Biometrical Department for End-Users |
Peter Herbertz |
source |
12 |
| SUGI |
1984 |
A General Approach to Decision Support Systems Utilizing the SAS System |
William Ingram III,
Thomas P. Rothrock |
source |
7 |
| SUGI |
1984 |
Applications of Computer Cartography for Marketing Research and Corporate Planning |
Vince Bartle,
John G. Blodgett,
Marius Janson,
L. Douglas Smith |
source |
|
| SUGI |
1984 |
Data Base Design for Decision Support Systems |
Gregory N. Smith |
source |
6 |
| SUGI |
1984 |
GENISYS-A Generalized Inventory System for Clinical Trial Data |
Pamela A. Frueh |
source |
5 |
| SUGI |
1984 |
Initial Experiences with the SAS System for Minicomputers |
C. David Hardison,
Edwin D. Suckstorff |
source |
6 |
| SUGI |
1984 |
Interactive SAS Use in Batch Mode: Making the SAS System User Friendly in a ROSCOE Batch Environment |
S. David Riba |
source |
3 |
| SUGI |
1984 |
SAS Applications to a Spring Wheat and Sunflower Yield Modeling Project |
Paul G. Held,
James Knuteson,
D. Patterson,
Michael Ulmer |
source |
4 |
| SUGI |
1984 |
SAS Programs for Reporting the Results of Bioequivalence Trials |
James T. Crowe Jr.,
Thaddeus J. Malicz |
source |
3 |
| SUGI |
1984 |
Statistics Automation: Using SAS Macros to Produce Report-Ready Statistical Analysis Tables |
Walter W. Offen |
source |
5 |
| SUGI |
1984 |
THECIS-The Clinical Information System |
Judith A. Burns,
Leon T. Hairie,
Thomas R. Hoffman |
source |
6 |
| SEUGI |
1983 |
Multivariate Data Analysis Library: "French Methods" SYSPAD |
Jean-Michel Gautier |
|
6 |
| SEUGI |
1983 |
SAS Applied to Statistical Databanks via a Command Language |
Inger Nilsson |
|
6 |
| SEUGI |
1983 |
Social Science Research and Statistical Packages |
Mogens Weinreich |
|
18 |
| SEUGI |
1983 |
The Information Centre in Rolls Royce |
Alan Kirkby |
|
4 |
| SUGI |
1983 |
Cooperative SAS Usage: University of Toronto and Toronto General Hospital |
E.D. Mitchell,
Cathy P. Tong,
R.D. Weisel |
source |
2 |
| SUGI |
1983 |
Development of an In-House SAS Basics Course |
Julie Stremel |
source |
5 |
| SUGI |
1983 |
Multivariate Data Analysis Library: "French Methods" SYSPAD |
Jean-Michel Gautier |
source |
6 |
| SUGI |
1983 |
SAS and APL: The Simultaneous Use of Both in Data Analysis |
Richard W. La Valley,
Eugene Mertz |
source |
|
| SUGI |
1983 |
SAS, A Truly International Software Package? |
Akira Kondo |
source |
4 |
| SUGI |
1983 |
Software for Statistical Graphics-An Overview |
Patricia M. Caporal,
C.J. Hahn |
source |
10 |
| SUGI |
1983 |
The Use of SAS in MIS-DSS Development |
David W. Johnson,
John R. Schultz,
Anthony A. Sinkula |
source |
6 |
| SUGI |
1983 |
Use of SAS/GRAPH in a Data Rich Organization: A Learning Experience |
Misa Gratton |
source |
|
| SUGI |
1982 |
A General Linear Models Approach for Comparing the Response of Several Species in Acute Toxicity Tests |
Karen L. Daniels,
Michael P. Farrell,
Jonathan C. Goyert,
Rodney H. Strand |
source |
6 |
| SUGI |
1982 |
A General Purpose TSO Interface to SAS Using SPF |
John L. Dickinson |
source |
|
| SUGI |
1982 |
A Pharmacokinetic Analysis System (PAS) |
Raymond P. Chen,
Daniel M. Wildman |
source |
|
| SUGI |
1982 |
An Integration of System 2000 and Statistical Analysis System (SAS) |
Roger E. Booker |
source |
7 |
| SUGI |
1982 |
Applications of SAS (FUNCAT) to the Analysis of Epidemiological/Survivorship Data |
Saeid B. Amini,
William R. Clarke,
Robert F. Woolson |
source |
9 |
| SUGI |
1982 |
Environmetrics of Synfuels: IV. Project Results Tracking System (PRIS) |
Karen L. Daniels,
Jonathan C. Goyert,
Rodney H. Strand,
Michael P. Farrell |
source |
9 |
| SUGI |
1982 |
SAS Report Generator: A SAS Program to Generate SAS Code |
Robert L. Anderson,
M.P Koranda |
source |
7 |
| SUGI |
1982 |
SCAN: An Interactive Graphics SAS Procedure for Specialized Correlation Analysis of Bivariate Data |
David A. DeNardis,
Robert N. Rodriguez |
source |
6 |
| SUGI |
1982 |
The Role of the Departmental Consultant in the Computer Center |
Eileen Driscoll |
source |
3 |
| SUGI |
1982 |
Training Statistical Consultants in a University Biostatistics Consulting Center |
Ronald G. Marks |
source |
4 |
| SUGI |
1982 |
Using SAS to Introduce University Administrators to Computing |
Andrew M. Smith |
source |
3 |
| SUGI |
1981 |
A Comparison of Graphics Packages Used with the Geoecology Data Base |
C. J. Emerson,
Martha K. Nungesser |
source |
|
| SUGI |
1981 |
Experience of Applying SAS in Engineering Analysis and Design |
Rhyn H. Kim |
source |
|
| SUGI |
1981 |
Processing 1980 Census Data: SAS versus CENSPAC |
Frank C. Dilorio,
Kenneth A. Hardy,
Judith M. Poole |
source |
|
| SUGI |
1981 |
Processing TESDATA Measurement Files with SAS |
J. William Mullen |
source |
7 |
| SUGI |
1981 |
Rules We Followed and Wish We Had Followed in Managing Datasets, Programs, and Printouts |
David H. Christiansen,
Keith E. Muller,
J.C. Smith |
source |
|
| SUGI |
1981 |
STATAN, a Conversational Interface to Facilitate SAS Usage or It Pays To Get Your SAS in Gear |
Anne M.Parkhurst |
source |
|
| SUGI |
1981 |
System 2000 Statistical Analysis System '81 |
Kirk Paul Lafler |
source |
7 |
| SUGI |
1981 |
Two-way Analysis of Variance in Computer Statistical Packages: A Comparison of SPSS, BMDP, and RUMMAGE to SAS GLM |
David W. Garton,
Kenneth L. Koonce |
source |
6 |
| SUGI |
1980 |
A Macro for Multivariate Randomization Analyses of Stratified Sample Data |
Ingrid A. Amara,
Gary G. Koch |
source |
11 |
| SUGI |
1980 |
Authoring an Interactive SAS Course |
Ione H. Cockrell,
Dorsey A. G. Condon |
source |
5 |
| SUGI |
1980 |
Conversational Data Input System: An Interface between VS BASIC and SAS |
Barbara Forsyth,
John David Rumpel |
source |
5 |
| SUGI |
1980 |
Management and Performance Reporting in an MVS Environment |
Mario M. Morino |
source |
|
| SUGI |
1980 |
Scientific Data Management and Analysis |
Steve Dassin,
John J. Frey,
George F. Griffin,
John McKenna |
source |
|
| SUGI |
1980 |
Slope Ratio Bioassay Using SAS |
Janet E. Field,
Rudolph S. Parrish,
Glenn O. Ware |
source |
|
| SUGI |
1980 |
Teaching Statistical Computing: A Comparison of Videotape and Classroom Methodologies |
John C. Boling |
source |
4 |
| SUGI |
1980 |
Teaching the Three Major Statistical Packages Simultaneously - SAS, SPSS, BMDP |
Chapman P. Gleason |
source |
6 |
| SUGI |
1980 |
The Storage and Display of Geographical Information Using SAS |
Kenneth A. Hardy,
James D. Hosking,
Grady B. Meehan |
source |
4 |
| SUGI |
1979 |
A SAS-AUTOGRP Interface for the Analysis of Hospital Discharge Data |
Michael B. Bracken,
Robert F. Elia,
Daniel H. Freeman Jr.,
Jean L. Freeman |
source |
7 |
| SUGI |
1979 |
Applications of SAS at Educational Institutions |
Emilio A. Icaza,
Kenneth L. Koonce |
source |
5 |
| SUGI |
1979 |
Cost Accounting an RJE Station with SAS |
Rodney H. Strand |
source |
5 |
| SUGI |
1979 |
The "Statistical Analysis System "as Implemented at EMBRAPA |
Dalton F. Andrade,
Cicero A. da Silva,
Enedino C. da Silva,
Gustavo M. Pimentel |
source |
4 |
| SUGI |
1979 |
The Role of Package Programs in Statistical Methods Courses |
Thomas A. Bubolz,
James E. Gentle |
source |
7 |
| SUGI |
1978 |
Conversational Instruction in the Statistical Analysis System |
Ione H. Cockrell,
Dorsey A. Glenn |
source |
4 |
| SUGI |
1978 |
Pinpointing Data with "DARTS " |
Mark R. Schultz |
source |
5 |
| SUGI |
1977 |
Accessing Census Summary Tape Files in SAS |
Daniel M. Chilko |
source |
3 |
| SUGI |
1977 |
Managing the Software/People Trade-Off |
Thomas D. Lutz |
source |
3 |
| SUGI |
1977 |
SAS 76 in Public Health Research |
Robin Layland |
source |
3 |
| SUGI.ONE |
1976 |
A Conversational Front End to SAS |
Julian Horwich,
Mark Phelps |
source |
5 |
| SUGI.ONE |
1976 |
Data Management for Environmental Research |
Rodney H. Strand |
source |
18 |
| SUGI.ONE |
1976 |
NPAR Using SAS 75 |
Daniel M. Chilko |
source |
4 |
| SUGI.ONE |
1976 |
Statistical and Data Support to a Heterogeneous User Community |
Marion C. Carter,
Richard C. Roistacher |
source |
14 |
| SUGI.ONE |
1976 |
The Relationship of SAS to Other Packages |
J. Philip Miller |
source |
8 |
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