| WUSS |
2026 |
Are We Winning the Vulnerabilities Battle? Measuring Cybersecurity Progress with SAS Viya Data Pipelines [presentation] |
Mike Krizan |
source |
14 |
| 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 |
From Raw to Compliant: Applying Domain-Specific SAS Macros for Data Cut-Off in Clinical Trials |
Ballari Sen |
source |
26 |
| WUSS |
2026 |
SAS Essentials II: Introduction to DATA Step Programming [presentation] |
Susan J. Slaughter |
source |
40 |
| PharmaSUG CN |
2026 |
AI-Native Real-Time SDTM Mapping and Exploration Agent |
Hao Chen,
Xuejie Zhou,
Haomin Yang,
Qianwang Wang |
source |
13 |
| PharmaSUG |
2026 |
A Standardized R Graph Library for Production-Ready Analysis Figures |
Chunting Zheng,
Margaret Huang,
Xindai Hu |
source |
19 |
| 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 Experience Using R, SASSY and Tidyverse For Clinical Trial Analysis, From A SAS Programmer Perspective |
David W. Franklin |
source |
27 |
| PharmaSUG |
2026 |
Chatting with Your Data, Wherever It Lives: Unlock Insights through Duck DB and Open File Formats |
Sundaresh Sankaran,
Mary Dolegowski |
source |
15 |
| PharmaSUG |
2026 |
Enhancing Quality and Efficiency in Clinical Programming with a Python-Based Automated File Comparison Tool |
Ratheesh Gunda |
source |
10 |
| 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 |
Friction to Flow: LLM-Based Automation of Clinical Data Workflows |
Pankaj Attri,
Matthew J. Becker |
source |
8 |
| PharmaSUG |
2026 |
Hero-in-the-Loop: A Super Squad Approach to SDTM Creation & Validation |
Julie Ann Hood |
source |
7 |
| PharmaSUG |
2026 |
It-s a Wonderful Lifecycle: Translating Statistical Programming into Modern Analytics Development |
Steve Nicholas |
source |
3 |
| PharmaSUG |
2026 |
Navigating Early Career Challenges in PK/ADA Statistical Programming |
Diyu Yang,
Sandeep Meesala |
source |
11 |
| PharmaSUG |
2026 |
One Study, Many Regulators: Submission-Ready Data Package for Multi-Region Filings |
Himanshu Patel,
Chintan Pandya |
source |
10 |
| PharmaSUG |
2026 |
Ready for Next Level SDTMs and ADaMs Compliance with End-to-End Processing? |
Sunil Kumar Gupta,
Tomás Sabat Stofsel |
source |
6 |
| PharmaSUG |
2026 |
SAS Programming techniques for efficiency and code optimization |
Jayanth Iyengar |
source |
27 |
| PHUSE US |
2026 |
Accelerating Study Insights: Agile Data Visualisation Using R-Shiny |
Lin Yuan,
Heather Howell |
source
presentation source |
6 |
| PHUSE US |
2026 |
AUTOCODE: Metadata-Driven Automation for Faster, Traceable SDTM and ADaM Programming |
Matthew Finnemeyer |
source
presentation source |
6 |
| PHUSE US |
2026 |
Beyond the Hype: Practical Guidance for LLM Adoption in Statistical Programming |
Michael Goedde |
source
presentation source |
9 |
| PHUSE US |
2026 |
Breaking Free from the xpt: Exploration of Dataset-JSON as an Alternative Transport File to Regulatory Agencies |
Benjamin Straub,
Samir Parmar |
source
presentation source |
8 |
| PHUSE US |
2026 |
Building Sustainable RBQM Frameworks: Challenges, Metrics and Real-World Results |
Nicole Stansbury |
source
poster source |
7 |
| PHUSE US |
2026 |
Business Event Triggers - The Next Level of Automation |
Marc Jantke |
source
presentation source |
6 |
| PHUSE US |
2026 |
CDISC 360i: From Vision to Implementation - Lessons Learned and the Road Ahead [presentation] |
Peter Van Reusel |
source |
23 |
| PHUSE US |
2026 |
Check Yourself: Edit Checks and Queries Made Easy with Shiny |
Maya Gans |
source
presentation source |
8 |
| PHUSE US |
2026 |
Evolve Clinical Data Management: A Python-Based Framework for Clinical Data Transformation with Generative AI Integration |
Mitul Patel,
Denis Sokolov |
source
presentation source |
5 |
| PHUSE US |
2026 |
Multi-Standard Submission - Process, Learnings and Recommendations for Best Practice |
Mukesh Garg |
source
presentation source |
8 |
| 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 |
Optimising Flexibility and Consistency in Statistical Programming for Platform Trials: Practical Approaches to Data Cut, SDTM, ADaM and TFL Setup |
Kelly Fang,
Zhen (Laura) Li |
source
poster source |
6 |
| PHUSE US |
2026 |
Problem-First Agentic AI: Transforming Statistical Computing with Purposeful Automation |
Rajesh Hagalwadi |
source
presentation source |
8 |
| PHUSE US |
2026 |
Ready for Next-Level SDTM and ADaM Compliance with End-to-End Processing? |
Sunil Kumar Gupta |
source
presentation source |
4 |
| PHUSE US |
2026 |
Reimagining SDTM Mapping with Agentic AI and Automation |
Nathan Johnson |
source
presentation source |
4 |
| 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 |
Scaling Interactive Applications for Clinical & RWE Insights Best Practices for Adoption, Compliance, and Long-Term Impact |
Chris McSpiritt Domino |
source
presentation source |
8 |
| PHUSE US |
2026 |
Straight to the Source: Interactive Visual Dashboards for Data Cleaning |
Daniel Smith |
source
presentation source |
8 |
| 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 APAC |
2026 |
CDISC 360i – Lessons Learned and Road Ahead [presentation] |
Peter Van Reusel |
source |
26 |
| PHUSE APAC |
2026 |
Elevating transparency in data standardization Applying XAI in SDTM, ADaM, and TLF Generation |
Shakila Jagadeesan |
source
presentation source |
10 |
| PHUSE APAC |
2026 |
End-to-End Continuous Integration and Deployment Pipeline for Multi Language Analytics Applications: A Clinical Data Management Case Study |
Avinash Patnaik,
Varun Sethuraman |
source
presentation source |
7 |
| PHUSE APAC |
2026 |
From XPT to JSON for submissions: Are we ready for the change? |
Poorna Suresh,
Bill Qubeck |
source
presentation source |
20 |
| PHUSE APAC |
2026 |
Harnessing the Power of Safety Database |
Ravichandra Hugar,
Aparna Sarju |
source
presentation source |
9 |
| PHUSE APAC |
2026 |
RbQM: An Intersection of Cross-Functional Collaboration of Clinical, Analytics, Statistics and Technology Domains for Better Clinical Trial Governance |
Abhishek Ghosh |
source
presentation source |
10 |
| PHUSE APAC |
2026 |
Signal First: A Data-Driven Approach to Safety Prioritization Using SAS and Tableau |
Jinu J. Nair,
Rubina Pathan |
source
poster source |
9 |
| 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 EU |
2025 |
Blockchain for Secure and Transparent Clinical Trials |
Raj Kumar |
source
presentation source |
8 |
| PHUSE EU |
2025 |
Building Reusable Precision Logic in SAS Using PROC FCMP |
Mariam Babayan,
Syuzanna Simonyan |
source
presentation source |
6 |
| PHUSE EU |
2025 |
Collaborative Industry Open-Source Solutions for Clinical Trial Quality Management |
Björn Koneswarakantha,
Frederik Collin |
source
presentation source |
9 |
| PHUSE EU |
2025 |
Disruption in Clinical Trials: How Conventional Roles Are Set to Change |
Amit Javkhedkar,
Kala Shivali |
source
presentation source |
7 |
| PHUSE EU |
2025 |
Modernising Clinical Data Science: Best Practices for a Unified, Governed SCE [presentation] |
Matthew Tendler |
source |
13 |
| PHUSE EU |
2025 |
More Science, Less Bookkeeping: Our Path to Hyper-Efficient ADaM Program Generation via AI, Process Improvements, and Good Old-Fashioned Programming |
Matthew Phelps,
Nicolai Skov Johnse |
source
presentation source |
10 |
| PHUSE EU |
2025 |
Reproducibility, Lineage and Control: Building a Traceability Framework for the Modern Clinical Trial |
Bill Qubeck,
Shilpa Sood |
source
poster source |
6 |
| PHUSE EU |
2025 |
rock and roll - Deliverables driven by standardized data specifications |
Svetlana Freiberga,
Mounika Suddapalli |
source
poster source |
8 |
| PHUSE EU |
2025 |
Small Application for Big Change: Data Integrity and Compliance Through Automated Decision Tracking with Shiny |
Olena Olishevska,
Mika Mäkinen |
source
poster source |
9 |
| PHUSE EU |
2025 |
Turning Data into Deliverables: Automating Biometrics from Metadata to TFLs |
Inderjeet Arora |
source
presentation source |
9 |
| PHUSE EU |
2025 |
Using Visual Dashboards to Improve Data Accuracy |
Daniel Smith |
source
poster source |
8 |
| MWSUG |
2025 |
An analysis of Emergency Department Visits for the 10 Health Division Regions across the US during the period 2018 2025 [presentation] |
Baoyuan Zhou |
source |
24 |
| MWSUG |
2025 |
Make You Holla' Tikka Masala: Creating User-Defined Informats Using the PROC FORMAT OTHER Option To Call User-Defined FCMP Functions That |
Troy Martin Hughes |
source |
10 |
| MWSUG |
2025 |
Prompt, Program, Submit: Generative AI for Faster SDTM, ADaM, and TLFs |
Matthew J. Becker,
Pankaj Attri |
source |
7 |
| SESUG |
2025 |
Automate in a DASH with SAS: Time Saving Techniques for Building Quality Improvement Dashboards |
Shavonne J. Standifer |
|
10 |
| SESUG |
2025 |
Becoming Trilingual: A Story of a SAS Programmer Learning R and Python |
Aaron Brown |
|
10 |
| SESUG |
2025 |
Ensure complete raw data to SDTM mapping: a SAS macro approach for quality control |
Cally Davidson,
Eric Howard |
|
8 |
| SESUG |
2025 |
Lookup Tables (LUT) in SAS and Data-Driven Programming |
Imelda C. Go,
Abbas S. Tavakoli |
|
17 |
| SESUG |
2025 |
Spring Cleaning for CSVs: Prepare for PROC IMPORT |
Brooke Ellen Delgoffe |
|
16 |
| SESUG |
2025 |
Versatile Graphic Presentation of Immunogenicity Analysis Results in Vaccine Studies with a Macro that Creates Multiple Forest Plots in One Output |
Hong Wang |
|
9 |
| WUSS |
2025 |
Prompt, Program, Submit: Generative AI for Faster SDTM, ADaM, and TLFs |
Matthew J. Becker |
source |
7 |
| WUSS |
2025 |
SAS Essentials II: Introduction to DATA Step Programming [presentation] |
Susan J. Slaughter |
source |
40 |
| PharmaSUG |
2025 |
A Customizable Framework in R for Presenting BICR Data in a User-Friendly Format |
Reneta Hermiz,
Jing Ji |
source |
14 |
| PharmaSUG |
2025 |
ADaM Fundamental Principles vs. Rules: Which to Follow, When, and Why? |
Sandra Minjoe,
Mario Widel |
source |
6 |
| 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 |
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 |
Change the way you think of Codelist - Optimize managing Organization Controlled Terminology with a meta-model and its features to manage Codelist in MDR |
Kairav Tarmaster |
source |
11 |
| PharmaSUG |
2025 |
Checking SDTM Datasets from Biostatistical Perspective |
Inka Leprince,
Elizabeth Li |
source |
14 |
| PharmaSUG |
2025 |
Data management and biostatistics synergy: how to achieve and what can be expected |
Diana Avetisian |
source |
11 |
| PharmaSUG |
2025 |
Does SDTM Validation Really Require Double Programming? |
Sunil Kumar Gupta,
Tomás Sabat Stofsel |
source |
5 |
| PharmaSUG |
2025 |
Efficient CDISC Controlled Terminology Mapping: An R-Based Automation Solution |
Yunsheng Wang |
source |
8 |
| PharmaSUG |
2025 |
Ensuring Data Integrity: Techniques for Validating SDTM Datasets in Clinical Research |
Amy Welsh |
source |
8 |
| PharmaSUG |
2025 |
Follow the Yellow Brick Road: Finding the Critical Path for a Study-s Lifespan |
Jake Gallagher |
source |
4 |
| PharmaSUG |
2025 |
Guidance from the FDA authored "Submitting Patient-Reported Outcome Data in Cancer Clinical Trials" and recommendations for their implementation in study CDISC COA data. |
Charity Quick |
source |
14 |
| PharmaSUG |
2025 |
Macro to Compare ADaM Spec Derivations Against Available SDTM Data |
Ingrid Shu,
Kexin Guan,
Jeff Xia |
source |
9 |
| PharmaSUG |
2025 |
Stop Making More Physical Copies of Your Data: A Modern Approach to Traceability and Fidelity |
Anthony Chow,
Robert Garelick |
source |
8 |
| PharmaSUG |
2025 |
The Many Use Cases of Standardized Data and Metadata |
Sanjiv Ramalingam |
source |
4 |
| PharmaSUG |
2025 |
Traceability and AI for Improved Understanding, Communication and QC of Clinical Trials |
Tomás Sabat Stofsel |
source |
5 |
| PharmaSUG |
2025 |
Which ADaM Data Structure Is Most Appropriate? Gray Areas in BDS and OCCDS. |
Veronica Gonzalez |
source |
15 |
| PharmaSUG |
2025 |
You don-t have to handle the truth! Three Things to Know about Synthetic Data |
Catherine Briggs,
S. Robert Collins,
Sundaresh Sankaran |
source |
7 |
| PHUSE US |
2025 |
A Guided User Experience for Automated Mapping |
Nathan Johnson |
source
presentation source |
9 |
| PHUSE US |
2025 |
Biomedical Concepts: What Are They and Why Should I Care? |
Stuart Malcolm |
source
presentation source |
7 |
| PHUSE US |
2025 |
Challenges of Genomic Data in Clinical Trials |
Hong Zheng,
Lingsong Yun |
source
presentation source |
8 |
| PHUSE US |
2025 |
Considerations for the Submission of RWD using CDISC with Insights from HL7 FHIR and OMOP |
Ingeborg Holt,
Sarah Ferko,
Jeffrey M. Abolafia |
source
presentation source |
15 |
| 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 |
Elevate Your Game: Leveling Up SDTM Validation with the Magic of Data Managers |
Julie Ann Hood |
source
poster source |
4 |
| PHUSE US |
2025 |
Enable and Automate: A Technical Roadmap Defining CDISC's Path to End-to-End Automation |
Samuel Hume |
source
presentation source |
8 |
| PHUSE US |
2025 |
Ensuring Data Integrity: A Three Step Approach to Clinical Dashboard Validation |
River Meckstroth |
source
presentation source |
7 |
| PHUSE US |
2025 |
From Roadblocks to Roadmaps: Overcoming Challenges in Registry Data Reporting |
Sivasankar Konda,
Neha Srivastava |
source
presentation source |
4 |
| 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 |
Mapping OMAP Data to SDTM - Use Case for RWD in CAR-T Registry Studies |
Kai Deng,
Joe Xi |
source
presentation source |
5 |
| 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 |
SDTM Specification Automation Using an ML Approach to Provide Mappings |
Benzi Mathew,
Jaya Simha Inampudi |
source
presentation source |
5 |
| PHUSE US |
2025 |
The Role of Quantitative Bias Analysis (QBA) in Ensuring the Reliability of Real-World Evidence (RWE) in Regulatory Submissions |
Brian Gillette,
Tasha Nagamine |
source
presentation source |
6 |
| PHUSE US |
2025 |
Using the USDM and Ensuring Governance and Traceability to unlock the potential of Real-World Data sources for regulatory submissions |
Berber Snoeijer |
source
presentation source |
12 |
| PHUSE US |
2025 |
Utility Macro for Ensuring Consistent Updates of CRF Data in SDTM |
Naren Surampalli |
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 |
| MWSUG |
2024 |
Best Practices for Efficiency and Code Optimization in SAS programming |
Jayanth Iyengar |
source |
20 |
| MWSUG |
2024 |
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 |
11 |
| MWSUG |
2024 |
Using SAS To Manage And Maintain Your Data Repository [presentation] |
Jose Centeno |
source |
16 |
| PHUSE EU |
2024 |
A Guided User Experience for Automated Mapping |
Achilleas Zaras |
source
presentation source |
9 |
| PHUSE EU |
2024 |
Biomarkers Unleashed: A Programming Pipeline from Chaos to Clarity in Genomic Data |
Saskia Ständler,
Lea Zittlau |
source
presentation source |
10 |
| PHUSE EU |
2024 |
Considerations for the Submission of RWD using CDISC with Insights from HL7 FHIR and OMOP |
Jeffrey M. Abolafia,
Sarah Ferko,
Ingeborg Holt |
source
presentation source |
13 |
| PHUSE EU |
2024 |
Data Curation Beyond Today's Standards |
Catharina Dahlbo,
Eva Kelty |
source
poster source |
5 |
| PHUSE EU |
2024 |
From Source to Submission: Getting the Best of Multiple Standards |
Jules Van der Zalm,
Berber Snoeijer |
source
presentation source |
4 |
| 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 |
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 |
Making SDTM/ADaM CRT Packages Submission Ready |
Phillip Spowart |
source
presentation source |
10 |
| PHUSE EU |
2024 |
Navigating and Building Bridges: A Framework for Clinical Programming Using Open-Source Tools |
Yash Ankurbhai Shah,
Kavitha Allala |
source
presentation source |
8 |
| SESUG |
2024 |
Comparative Tools in SAS: Analyzing Self-Reported versus Imputed Values |
Neesha Nathwani,
Sarah Woodruff |
source |
30 |
| WUSS |
2024 |
Will statistical programmers be replaced by Artificial Intelligence? [presentation] |
Junying Zhang |
source |
20 |
| PharmaSUG CN |
2024 |
A Method to Compare the RTF Files in Batch Mode and Generate a Checklist and Tracked RTF Files as Comparison Outputs |
Sachiel Li,
Xinran Tang |
source |
11 |
| PharmaSUG CN |
2024 |
An Automatic SDTM Platform: Create Your SDTM Since Case Report Form is Ready! |
Mingyue Zhu,
Wei Wang,
Mingfeng Zhou |
source |
12 |
| PharmaSUG CN |
2024 |
Introduction of Ophthalmic Examinations and the Preparation of SDTM OE Using SDTM IG 3.3 |
Shuang Qiu |
source |
15 |
| PharmaSUG CN |
2024 |
Practice in Creating an R package for SDTM |
En Wang,
Longfei Li,
Xinyan Lai,
Qian Duan |
source |
5 |
| PharmaSUG CN |
2024 |
Programming Activities of Conducting Data Masking in Open-Label Study |
Xinyun Gao |
source |
6 |
| PharmaSUG CN |
2024 |
Return to baseline status of the worst elevated liver function tests |
Yuan Sun,
Tingting Zhang |
source |
10 |
| 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 New Approach to Automating the Creation of the Subject Visits (SV) Domain |
Xiangchen (Bob) Cui,
Jessie Wang,
Min Chen |
source |
24 |
| PharmaSUG |
2024 |
A New Way to Automate Data Validation with Pinnacle 21 Enterprise CLI in LSAF |
Crystal Cheng |
source |
7 |
| PharmaSUG |
2024 |
AutoSDTM Design and Implementation With SAS Macros |
Chengxin Li |
source |
10 |
| PharmaSUG |
2024 |
Bridging AI and Clinical Research: A New Era of Data Management with ChatGPT |
Illia Skliar |
source |
12 |
| 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 |
Elevate Your Game: Leveling Up SDTM Validation with the Magic of Data Managers |
Julie Ann Hood,
Jen Manzi |
source |
5 |
| PharmaSUG |
2024 |
Exploring the Application of FDA Medical Query (FMQ) in Visualizing Adverse Event Data |
Tongda Che,
Danfeng Fu |
source |
12 |
| PharmaSUG |
2024 |
Game changer! The new CDISC ADaM domain ADNCA for PK/PD data analysis |
Santosh Ranjan |
source |
7 |
| PharmaSUG |
2024 |
Oncology ADaM Datasets Creation Using R Programming: A Comprehensive Approach |
Ishwar Chouhan |
source |
29 |
| PharmaSUG |
2024 |
Periodic safety reports of clinical trials |
Murali Kanakenahalli,
Annette Bove,
Smita Sehgal |
source |
8 |
| PharmaSUG |
2024 |
Quality Assurance within Statistical Programming: A Systemic Way to Improve Quality Control |
Todd Case,
Margaret Huang |
source |
4 |
| PharmaSUG |
2024 |
Source Data Quality Issues in PopPK/PD Dataset Programming: a Systematic Approach to Handle Duplicates |
Ibrahim Priyana,
Ellen Winckelmans |
source |
10 |
| PharmaSUG |
2024 |
Submitting Patient-Reported Outcome Data in Cancer Clinical Trials - Guidance for Industry Technical Specifications Document [presentation] |
Flora Mulkey |
source |
48 |
| PharmaSUG |
2024 |
Translation from statistical to programming: effective communication between programmers and statisticians |
Diana Avetisian |
source |
10 |
| PharmaSUG |
2024 |
Unravelling the SDTM Automation Process through the Utilization of SDTM Transformation Template |
Lakshmi Mantha,
Inbasakaran Ramesh |
source |
11 |
| PHUSE US |
2024 |
A Programmer's Perspective on Navigating the Hurdles of Investigator-Sponsored Research (ISR) Trials |
Jyotsna Lakshmikumar |
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 |
Effective Workflow Process: Rapid SDTMs and Compliance Dashboards |
Sunil Kumar Gupta,
Harinarayan Gopichandra |
source
poster source |
5 |
| PHUSE US |
2024 |
Effortless Table Generation: A SAS Macro for Streamlining Your Workflow |
Zhen (Laura) Li |
source
presentation source |
12 |
| PHUSE US |
2024 |
Electronic Clinical Outcome Assessment (eCOA) in SDTM: Challenges and Solution |
Shivam Kumar |
source
presentation source |
5 |
| PHUSE US |
2024 |
Eliminating Duplicative Maintenance of Statistical Programs In Parallel Analyses Using a Single Control File |
Kavitha Boinapally |
source
poster source |
4 |
| PHUSE US |
2024 |
How to Monitor SDTM Data Health |
Amanda Cross |
source
presentation source |
8 |
| PHUSE US |
2024 |
My Data Are Too Good to Be True! Should I Worry About Fraud or Sloppiness? |
Johann Proeve |
source
presentation source |
9 |
| PHUSE US |
2024 |
Post-Pandemic Trends in Study Designs |
Charumathy Sreeraman,
Jisha George |
source
presentation source |
7 |
| PHUSE US |
2024 |
Scaling ECAs from Projects to the Enterprise: Multicentre, Multisource Infrastructure for External Control Arms |
Jussi Leinonen,
Mayur Saxena |
source
presentation source |
4 |
| PHUSE US |
2024 |
The Many Use Cases of Standardized Data and Metadata |
Sanjiv Ramalingam |
source
presentation source |
4 |
| PHUSE EU |
2023 |
'Beep Beep': A Metadata Code Writer to Generate SAS Programs |
Giuseppe Di Monaco |
source
presentation source |
10 |
| PHUSE EU |
2023 |
A Robust Framework to Provide and Validate Real-Time SDTM Data |
Bremer Louw |
source
presentation source |
11 |
| PHUSE EU |
2023 |
Increasing Trend of Biomarker Analysis in Clinical Trials |
Anjali Ranga |
source
presentation source |
11 |
| PHUSE EU |
2023 |
Metadata-Driven ADaM R-Code Generation by Leveraging Automation Potential |
Thiago Figueiredo,
Waldemar Miller |
source
presentation source |
31 |
| PHUSE EU |
2023 |
Multiple Myeloma: Challenges in identifying regimen modification for a given line of Chemotherapy |
Mrityunjay Kumar,
Ephicacy Lifescience,
Shailesh Gupte |
source
presentation source |
7 |
| 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 |
Standardisation in a fast growing environment; MDR, EDC and other abbreviations |
Louella Schoemacher,
Jasmine Kestemont |
source
presentation source |
6 |
| 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 |
Traceability Confirmation at Your Fingertips [presentation] |
Shafi Chowdhury |
source |
16 |
| WUSS |
2023 |
Make You Holla' Tikka Masala: Creating User-Defined Informats Using the PROC FORMAT OTHER Option To Call User-Defined FCMP Functions That Facilitate Data Ingestion Data Quality |
Troy Martin Hughes |
source |
10 |
| WUSS |
2023 |
When ANY Function Will Just NOT Do |
Richann J. Watson,
Karl Miller |
source |
8 |
| SESUG |
2023 |
Best Practices for Efficiency and Code Optimization in SAS programming |
Jayanth Iyengar |
source |
20 |
| SESUG |
2023 |
Make You Holla' Tikka Masala: Creating User-Defined Informats Using the PROC FORMAT OTHER Option To Call User-Defined FCMP Functions That Facilitate Data Ingestion Data Quality |
Troy Martin Hughes |
source |
10 |
| PharmaSUG |
2023 |
A case study of a successful RTOR submission and approval for Rylaze |
Sudhir Kedare,
Dilip Nalla,
Kumud Kanneganti,
Jagan Mohan Achi |
source |
6 |
| 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 |
Automating SDTM: A metadata-driven journey. |
Keith Hibbetts |
source |
11 |
| PharmaSUG |
2023 |
Best Practices for Efficiency and Code Optimization in SAS programming |
Jayanth Iyengar |
source |
20 |
| PharmaSUG |
2023 |
Better CDISC Standards with Metadata Programming |
Sunil Kumar Gupta,
Abhishek Dabral |
source |
14 |
| PharmaSUG |
2023 |
Can We Do It Better? Real-Time Validation Of Sdtm Mapping Is Superior To Double Programming |
Daniel Rolo,
Bremer Louw |
source |
9 |
| PharmaSUG |
2023 |
Gear up the Metadata - Automating Patient Profile Generation, a Metadata Driven Programming Approach |
Tanmay Khole,
Aman Sharma,
Lili Li,
Durga Prasad Chinthapalli |
source |
20 |
| PharmaSUG |
2023 |
Hard Coding: What is it? Why Does It Matter? What Should You Do When Faced With Such A Request? |
Michael Nessly |
source |
4 |
| PharmaSUG |
2023 |
Have Meaningful Relationships: An Example of Implementing SDTM Special Purpose Data Set RELREC with a Many-to-Many Relationship |
Kaleigh Ragan,
Richann J. Watson |
source |
11 |
| 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 |
Make You Holla' Tikka Masala: Creating User-Defined Informats Using the PROC FORMAT OTHER Option To Call User-Defined FCMP Functions That Facilitate Data Ingestion Data Quality |
Troy Martin Hughes |
source |
10 |
| PharmaSUG |
2023 |
Traceability: Not just about Data |
Rohit Nagpal,
Kavitha Mullela |
source |
11 |
| PharmaSUG |
2023 |
Using P21 Checks to Help Your DM Out! |
Chad Fewell,
Jesse Beck |
source |
4 |
| PharmaSUG |
2023 |
Using R to Create Population Pharmacokinetic Dataset |
Yangwei Yan,
Prema Sukumar,
Neelima Thanneer |
source |
10 |
| PHUSE US |
2023 |
A Programmer's Point of View of Current and Future PD Detection T ools |
Meng Li |
source
presentation source |
6 |
| PHUSE US |
2023 |
Challenges Addressing CBER Guidance on Reactogenicity, from Collection to Analysis |
Sandra VanPelt Nguyen,
Emily Bernstein-Hanlon |
source
presentation source |
12 |
| PHUSE US |
2023 |
EDC Raw Data to SDTM Curation, Mapping and Automation with XBiom Tool |
Sunil Kumar Gupta,
Rahul Madhavan |
source
presentation source |
7 |
| PHUSE US |
2023 |
Metadata Driven Creation of TLF Programs by Using JSON Data File [presentation] |
Linshan Yuan,
Sheng-Wei Wang |
source
video |
18 |
| PHUSE US |
2023 |
Practical Application of Multiple Screenings/Enrollments |
Martha O'Brien,
Proma Debnath |
source
presentation source |
4 |
| PHUSE US |
2023 |
Reviewing External Vendor Data Transfer Specifications from a Programming Standpoint |
Mahesh Minnakanti |
source
presentation source |
5 |
| PHUSE US |
2023 |
Say No to Stale Data!! Implementation of Automated GxP Data Pipelines Using KNIME [presentation] |
Shiva Katepalli,
Jeffrey Xiong |
source
video |
30 |
| PHUSE US |
2023 |
Variations on a Theme. Let Me Count the Ways We Do Things Differently to Achieve the Same Goal [presentation] |
Andy Ratcliffe |
source
video |
21 |
| PHUSE EU |
2022 |
An Approach to Effectively Reproduce TFLs When Performing ADaM Conversion [presentation] |
Amine Khemiri,
Caroline Pelckmans |
source
video |
19 |
| PHUSE EU |
2022 |
Best Practices for Automated Delivery Set-up, from Raw Data to CRT, with Methods to Standardise and Streamline Programming and Delivery Processes [presentation] |
Daniel Carden |
source
video |
21 |
| 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 |
Minimising 'Data Loss' During Mapping of Raw Data to SDTM [presentation] |
John Monaghan |
source
video |
35 |
| PHUSE EU |
2022 |
Practical Implementation of Good Programming Practice and Other Theories in Macro Development |
Fred Ross |
source
presentation source |
4 |
| PHUSE EU |
2022 |
R Shiny to Drive Automation in Clinical Analysis and Reporting [poster] |
Jocelyn Wang,
Goutham Ghanta |
source |
1 |
| PHUSE EU |
2022 |
The Role of Data Analytics Functions in Studies Utilising RWD for Submissions [presentation] |
Mark Graham,
Ravi Bahia |
source
video |
15 |
| SESUG |
2022 |
Offensive Programming: A Threesome of Error-Throwing Macros |
Quentin McMullen |
source |
20 |
| SESUG |
2022 |
Statistical Analysis of School Shootings in the United States as Stochastic Terrorism |
David J. Corliss |
source |
8 |
| WUSS |
2022 |
Best Practices for Efficiency and Code Optimization in SAS programming |
Jayanth Iyengar |
source |
21 |
| WUSS |
2022 |
Child Data Set: An Alternative Approach for Analysis of Occurrence and Occurrence of Special Interest |
Lindsey Xie,
Richann J. Watson,
Jinlin Wang,
Lauren Xiao |
source |
15 |
| WUSS |
2022 |
Cooking in SAS Viya |
Charu Shankar |
source |
10 |
| WUSS |
2022 |
TrackCHG: A SAS Macro to Colorize and Track Changes Between Data Transfers in Subject-Level Safety Listings |
Inka Leprince,
Elizabeth Li,
Carl Chesbrough |
source |
21 |
| PharmaSUG |
2022 |
ADaM Child Data Set: An Alternative Approach for Analysis of Occurrence and Occurrence of Special Interest |
Lindsey Xie,
Richann J. Watson,
Jinlin Wang,
Lauren Xiao |
source |
15 |
| PharmaSUG |
2022 |
Applying Agile Methodology to Statistical Programming |
Gina Boccuzzi |
source |
5 |
| PharmaSUG |
2022 |
Automation of Variable Name and Label Mapping from Raw Data to Analysis Data Standards |
Xingshu Zhu,
Bo Zheng,
Li Ma |
source |
9 |
| PharmaSUG |
2022 |
How to utilize the EC domain to handle complex exposure data |
Varsha Korrapati,
Johnny Maruthavanan |
source |
8 |
| PharmaSUG |
2022 |
Pharmacokinetics Concentration Data Deciphered - Presenting an Oncology Case Study |
Nikita Sathish |
source |
9 |
| PharmaSUG |
2022 |
SAS Macro to Colorize and Track Changes Between Data Transfers in Subject-Level Listings |
Inka Leprince,
Elizabeth Li,
Carl Chesbrough |
source |
19 |
| PHUSE US |
2022 |
Automating Analysis Result Metadata [presentation] |
Ghanshyam Jangid |
source
video |
17 |
| PHUSE US |
2022 |
Incorporating Immunogenicity Data from Various Analyzing Labs [presentation] |
Elisabeth van Son-Palmen,
Gunasekaran Subramaniam |
source |
19 |
| PHUSE US |
2022 |
Metadata-driven Case Report Tabulation for Regulatory Submissions |
Jacques Lanoue,
Rajashekar Thota |
source
presentation source |
8 |
| PHUSE EU |
2021 |
Advanced Excel Specification for Automatic SDTM Generation |
Aleksandra Gorbunova,
Ilya Mishchenko |
source
video
presentation source |
10 |
| 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 |
Automated creation of a mapping specification for a pooled database |
Thomas Wollseifen |
source
video
presentation source |
12 |
| PHUSE EU |
2021 |
Does No Errors Equal High Quality? [presentation] |
Julie Solbjerg Appel,
Sanna Herrgård |
source
video |
23 |
| PHUSE EU |
2021 |
Standing Room Only: RW08: The Convenient Structure of the OMOP CDM [presentation] |
George Allerston,
Khaleeq Mannan |
source |
20 |
| SESUG |
2021 |
PROC FORMAT for Scrappy SAS Users and Posh Programmers |
Rachel Straney |
source |
12 |
| PHUSE US |
2021 |
Controlled Terminology Best Practices [presentation] |
Sarah Angelo |
source
video |
29 |
| PHUSE US |
2021 |
Metadata-based Auto-programming by Python and SAS [presentation] |
Harry Chen |
source
video |
10 |
| PHUSE US |
2021 |
Patient Registries - New Gold Standard for Real World Data [presentation] |
Lavanya Peddibhotla,
Sivasankar Konda |
source
video |
14 |
| PHUSE US |
2021 |
Planning and Execution of Real-world Data Evidence Analysis |
Nicole Thorne,
Ramesh Sundaram |
source
video
presentation source |
6 |
| PHUSE US |
2021 |
R Shiny Application for the PHUSE Open Data Repository [presentation] |
Hanming Tu |
source
video |
15 |
| PHUSE US |
2021 |
Regulatory Update & Townhall [presentation] |
Ethan Chen |
source |
28 |
| PHUSE US |
2021 |
Tipping the Scale: Moving from Scaling Experts to Balancing them with Novel Technologies [presentation] |
Christopher J. Colangelo |
source
video |
12 |
| PHUSE US |
2021 |
Using Central Monitoring to Mitigate Data Quality Risk during the COVID-19 Pandemic [presentation] |
Adrienne Strickler,
Anna Wojcik |
source
video |
21 |
| PharmaSUG |
2021 |
A Lead Programmer-s Guide to a Successful Submission |
Pranav Soanker,
Santosh Shivakavi |
source |
8 |
| PharmaSUG |
2021 |
ADaM-like Dataset: how to do big things in a short time |
Oksana Mykhailova,
Andrii Klekov |
source |
7 |
| PharmaSUG |
2021 |
First Time Creating a Submission Package? Don-t Worry, We Got You Covered! |
Lyma Faroz |
source |
10 |
| PharmaSUG |
2021 |
Only Get What You Need - To Simplify Analysis Data Validation Report from PROC COMPARE Output |
Wenjun He |
source |
12 |
| PharmaSUG |
2021 |
PROC FUTURE PROOF v1.1 - Linked Data |
Amy Gillespie,
Susan Kramlik,
Suhas R. Sanjee,
Jindřich Mynarz,
Danfeng Fu |
source |
12 |
| PharmaSUG |
2021 |
When Should I Break ADaM Rules? |
Sandra Minjoe |
source |
8 |
| SGF |
2021 |
Harnessing Raw Data From Submission Forms to Gauge Food Insecurity Among College Students |
Zoraya Cruz-Bonilla |
source
presentation |
12 |
| SGF |
2021 |
Transcoding: Understand, Troubleshoot, and Resolve a Most Mysterious SAS Error |
Yun (Julie) Zhuo |
source
presentation |
14 |
| PHUSE EU |
2020 |
Implementing FAIR in OHDSI: Challenges and Opportunities in EHDEN [presentation] |
Tess Korthout |
source
video |
23 |
| PHUSE EU |
2020 |
Power BI in Clinical Data Exploration: Powerful Visuals that Answer Relevant Questions |
Roxane Debrus |
source
video
presentation source |
11 |
| PHUSE EU |
2020 |
The Good? The Bad? Or the Ugly? CDISC eSubmission Packages in Practice [presentation] |
Artur Krupa |
source
video |
26 |
| SGF |
2020 |
Automatically Loading CAS Tables from SAS Data Integration Studio Using SAS Viya REST APIs |
Oscar Simionati,
Ervin Wilneder |
source |
9 |
| SGF |
2020 |
Coding in SAS Viya |
Charu Shankar |
source |
18 |
| SGF |
2020 |
Data Preparation Techniques for Cloud-Based Data Sources |
Jennifer L. Nenadic |
source |
11 |
| SGF |
2020 |
Data Standardization Using SAS Health Data Mapper |
Eric Bolender |
source |
14 |
| SGF |
2020 |
Explanatory Machine Learning Model Plots for Epidemiological and Real-World Evidence Studies |
David Olaleye |
source |
22 |
| SGF |
2020 |
How to Master a Risk Data Vault Using SAS Data Integration Studio |
Linus Hjorth |
source |
11 |
| SGF |
2020 |
Reading in a Comma Delimited File with a Data Dictionary |
Kalyani Telu |
source |
6 |
| SGF |
2020 |
The New solveBlackbox Action in SAS Optimization 8.5 |
Edward P. Hughes |
source |
14 |
| SGF |
2020 |
Your Data Will Go On: Practice for Character Data Migration |
Edwin Xie |
source |
13 |
| PharmaSUG |
2020 |
A Novel Solution for Converting Case Report Form Data to SDTM using Configurable Transformations |
Sara Shoemaker,
Matthew Martin,
Robert Kleemann,
David Costanzo,
Tobin Stelling |
source |
12 |
| PharmaSUG |
2020 |
Assessing Performance of Risk-based Testing |
Amber Randall,
Bill Coar |
source |
11 |
| PharmaSUG |
2020 |
Creating SDTMs and ADaMs CodeList Lookup Tables |
Sunil Kumar Gupta |
source |
8 |
| PharmaSUG |
2020 |
Metadata-driven Modular Macro Design for SDTM and ADaM |
Ellen (Zihui) Lin,
Aditya Tella,
Yeshashwini Chenna,
Michael Hagendoorn |
source |
9 |
| PharmaSUG |
2020 |
Preparing a Successful BIMO Data Package |
Elizabeth Li,
Carl Chesbrough,
Inka Leprince |
source |
20 |
| PharmaSUG |
2020 |
Untangling the Subject Elements Domain |
Christine McNichol |
source |
8 |
| PHUSE US |
2020 |
An automated code translation approach in SDTM specifications using %translate macro |
Hrideep Antony |
source
presentation source |
7 |
| PHUSE US |
2020 |
Data Compliance: Hidden Benefits |
Priyanka Adusumilli |
source |
3 |
| PHUSE US |
2020 |
Data Exchange in Clinical Trial - Programming Perspective |
Chao Wang |
source
presentation source |
5 |
| PHUSE US |
2020 |
Data Load Automation |
Jennifer H. Desai |
source
presentation source |
4 |
| PHUSE US |
2020 |
Data Standards Used for Electronic Submission of Real-World Evidence in New Drug Application (NDA) |
Nicole Thorne,
Kathy Wu |
source
presentation source |
10 |
| 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 |
Machine Learning-AI is the Future - What Now? |
Priyanka Adusumilli,
Priyank Patel |
source
poster source |
8 |
| PHUSE US |
2020 |
Mind the Gap: Raw Data Model |
Julie Smiley |
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 |
Rerouting Your Risk-based Monitoring Strategy: Overcoming Implementation Roadblocks with New Technologies and Approaches |
Jonathan Andrus |
source
presentation source |
9 |
| PHUSE US |
2020 |
The Elusive Goal of Automation in SDTM Mapping: A CRO perspective |
Sridhar Vijendra,
Ephicacy Lifescience |
source
presentation source |
6 |
| PHUSE US |
2020 |
Untangling the Subject Elements Domain |
Christine McNichol |
source
presentation source |
7 |
| PHUSE EU |
2019 |
Addressing the Gap in Data Standards: Introducing the Aggregation Layer |
Claudio Garutti,
Marko Bomyer |
source
presentation source |
11 |
| PHUSE EU |
2019 |
ADSL - Friend or Foe? |
Jørgen Mangor Iversen |
source
presentation source |
8 |
| PHUSE EU |
2019 |
Challenges Involved with Using Legacy Clinical Trial Study Data During Integration |
Adebola Opasanya |
source
poster source |
8 |
| PHUSE EU |
2019 |
Data Anonymisation & Risk Assessment - Process Map and Automation Efforts |
Lukas Kniola |
source
poster source |
7 |
| PHUSE EU |
2019 |
Early experiences using SDTM to organize clinical data collected using a physical activity tracker |
Martin Gram,
Gianluca Mortari |
source
presentation source |
13 |
| PHUSE EU |
2019 |
End-to-end SDTM Automation: A Metadata-centric Approach (winner) |
Roman Radelicki |
source
presentation source |
12 |
| PHUSE EU |
2019 |
Formedix On: Advanced Metadata Management and Data Conversion [presentation] |
Kevin Burges |
source |
47 |
| PHUSE EU |
2019 |
Harmonising SDTM at the Source: Two Years Later |
Helen Scanlon,
Sue Huxtable |
source
presentation source |
11 |
| PHUSE EU |
2019 |
Janssen's Journey Towards a Culture of Innovation |
Sumesh Kalappurakal,
Sangeeta Bhattacharya |
source
presentation source |
7 |
| PHUSE EU |
2019 |
Mapping Raw Data to SDTM Define Using the SAS Clinical Standards Toolkit |
Andrew Bullivant |
source
presentation source |
7 |
| PHUSE EU |
2019 |
Programming in the World of PK: Guidance for the Beginner |
Paige Lewis |
source
poster source |
7 |
| PHUSE EU |
2019 |
SDTM Validation Tool |
Anamaria Calai |
source
presentation source |
12 |
| PHUSE EU |
2019 |
The Trials and Tribulations of Automated SDTM Delivery |
Edward R. Jones |
source
presentation source |
5 |
| PHUSE EU |
2019 |
Use of FHIR in Clinical Research: From Electronic Medical Records to Analysis |
Jeffrey M. Abolafia,
Priya Gopal,
Samuel Hume |
source
presentation source |
12 |
| SESUG |
2019 |
Macroception: Maximizing the Capacity of your Macro Variables |
Connor Cosenza |
source |
8 |
| SESUG |
2019 |
PROC SQL for PROC SUMMARY Stalwarts |
Christianna S. Williams |
source |
18 |
| SCSUG |
2019 |
Top SAS Architecture Pitfalls: Lessons Learned the Hard Way |
Margaret A. Crevar |
source |
3 |
| PharmaSUG |
2019 |
ADaM 1.1 Compliant ADEVENT and ADTTE development in a Cardiovascular Study |
Chao Su |
source |
6 |
| PharmaSUG |
2019 |
Auto-generation of Clinical Laboratory Unit Conversions |
Alan Meier |
source |
9 |
| PharmaSUG |
2019 |
Automate the Process to Ensure the Compliance with FDA Business Rules in SDTM Programming for FDA Submission |
Xiangchen (Bob) Cui,
Hao Guan,
Min Chen,
Letan (Cleo) Lin |
source |
16 |
| PharmaSUG |
2019 |
Begin with the End of Validation: Adapting QbD Approach in Statistical Programming to Achieve Quality and Compliance Excellence |
Linghui Zhang |
source |
8 |
| PharmaSUG |
2019 |
Best Practices in Data Standards Governance |
Melissa R. Martinez |
source |
4 |
| PharmaSUG |
2019 |
Camouflage your Clinical Trial with Machine Learning and AI |
Ajith Baby Sadasivan,
Limna Salim,
Akhil Vijayan,
Anoop Ambika |
source |
10 |
| PharmaSUG |
2019 |
CBER Data Standards Update and BioCompute Progress |
Elaine Thompson |
source |
27 |
| PharmaSUG |
2019 |
Common Pinnacle 21 Report Issues: Shall we Document or Fix? |
Ajay Gupta |
source |
11 |
| PharmaSUG |
2019 |
Compare and conquer SDTM coding |
Phaneendhar Gondesi |
source |
5 |
| PharmaSUG |
2019 |
Considerations in Effectively Generating PK Analysis Input Datasets |
Jianli Ping |
source |
10 |
| PharmaSUG |
2019 |
Dataset Specifications: Recipes for Efficiency and Quality |
David A. Scocca |
source |
7 |
| PharmaSUG |
2019 |
Designing Flexible Data Standards Models |
Melissa R. Martinez |
source |
4 |
| PharmaSUG |
2019 |
Developing Analysis & Reporting Standards For Pharmaco-Epidemiology Observational Studies |
Bo Zheng,
Xingshu Zhu |
source |
5 |
| PharmaSUG |
2019 |
Forewarned is forearmed or how to deal with ADSL issues |
Anastasiia Oparii |
source |
16 |
| PharmaSUG |
2019 |
Interactive TLFs - A Smarter Way to Review your Statistical Outputs |
Bhavin Busa |
source |
5 |
| 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 |
Non-Clinical (SEND) Reference Guide for Clinical (SDTM) Programmers |
Dharmendra Tirumalasetti,
Bhavin Busa |
source |
6 |
| PharmaSUG |
2019 |
Practices in CDISC End-to-End Streamlined Data Processing |
Chengxin Li |
source |
14 |
| PharmaSUG |
2019 |
Progression-Free Survival (PFS) Analysis in Solid Tumor Clinical Studies |
Na Li |
source |
14 |
| PharmaSUG |
2019 |
Raw data sets tracker: Time and project management based on the volume of available clinical data using SAS software |
Girish Kankipati |
source |
10 |
| PharmaSUG |
2019 |
Using the PRXCHANGE Function to Remove Dictionary Code Values from the Coded Text Terms |
Lynn Mullins |
source |
4 |
| PharmaSUG |
2019 |
Vendor's Guide to Consistent, Reliable, and Timely CDISC Deliverables |
Dharmendra Tirumalasetti,
Santosh Reddy Lekkala,
Bhavin Busa |
source |
5 |
| SGF |
2019 |
Analyzing Structural Causal Models using the CALIS Procedure |
Banoo Madhanagopal,
John Amrhein |
source |
23 |
| SGF |
2019 |
Augmented Reality (Ar) Predictive maintenance System with Artificial Intelligence (AI) for Industrial Moblie Robot |
Yee Yang Tay,
Ye Sheng Koh,
Marvin Dares |
source |
12 |
| SGF |
2019 |
Automate in a DASH with SAS: Time Saving Techniques for Building Quality Improvement Dashboards |
Shavonne J. Standifer |
source |
10 |
| SGF |
2019 |
Causal Analyses Using Structural Equation Models |
Banoo Madhanagopal,
John Amrhein |
source |
23 |
| SGF |
2019 |
Collaboration Calibration: How SAS Data Scientists Collaborate Effectively Using SAS Viya |
Weston McManus,
Allison Becker |
source |
11 |
| SGF |
2019 |
Dynamically Assigning Length to Transposed Variables |
Ethan Ritchie |
source |
5 |
| SGF |
2019 |
The Transformation of Educational Data Using SAS : Introducing Intervention Analytics! |
Sean W. Mulvenon |
source |
10 |
| SGF |
2019 |
Top SAS Architecture Pitfalls: Lessons Learned the Hard Way |
Margaret A. Crevar |
source |
3 |
| PHUSE US |
2019 |
A Future 'View' of Digital Data from Wearable Devices |
Daniel Schramek |
source
presentation source |
11 |
| PHUSE US |
2019 |
An Open Clinical Data Quality Framework |
Vineet Jain |
source
presentation source |
11 |
| PHUSE US |
2019 |
Best Practices in Data Standards Governance |
Melissa R. Martinez |
source
presentation source |
3 |
| PHUSE US |
2019 |
CDISC in Phase I/II Studies: Case Studies in Adopting Standards |
Emily Woolley,
Amber Randall Scharp |
source
presentation source |
7 |
| PHUSE US |
2019 |
Don't Let Your Data Handle You: A Novel Approach to Clinical Programming |
Jorine Putter |
source
presentation source |
10 |
| PHUSE US |
2019 |
End-to-End SDTM Automation: A Metadata-centric Approach |
Roman Radelicki,
Swapna Pothula |
source
presentation source |
12 |
| PHUSE US |
2019 |
Formedix On: Advanced Metadata Management Now With Data! [presentation] |
Kevin Burges,
Steven Benham |
source |
45 |
| PHUSE US |
2019 |
From Source Data to SDTM: Enabling a Semi-automated Conversion |
Pieter Blomme |
source
presentation source |
4 |
| PHUSE US |
2019 |
How to Take the Risk Out of Risk-based Monitoring |
Shafi Chowdhury,
Nurahamid Siddiki |
source
presentation source |
4 |
| PHUSE US |
2019 |
Optimizing Over Time Plots Via Analytics |
Kishore Pothuri,
Mayank Choudhary |
source
poster source |
5 |
| PHUSE US |
2019 |
Proof of Concept (PoC) Development of Safety Visual Analytics (SVA) Using R Shiny and SAS |
Rinki Jajoo |
source
presentation source |
9 |
| PHUSE US |
2019 |
Stay Relaxed... A Utility to Auto-create Specification! |
Kaveri Pachiappan |
source
poster source |
7 |
| PHUSE US |
2019 |
Use of FHIR in Clinical Research: From Electronic Medical Records to Analysis |
Priya Gopal |
source
presentation source |
12 |
| PHUSE EU |
2018 |
A Proprietary CDASH/SDTM-hybrid Data Model to Expedite Clinical Data Review |
Lieke Gijsbers,
Tom Van Der Spiegel |
source
presentation source |
6 |
| PHUSE EU |
2018 |
Automated Creation of Submission-Ready Artifacts [presentation] |
Silas McKee,
Lourdes Devenney |
source |
15 |
| PHUSE EU |
2018 |
Automating SDTM - Get it Prepared with Your Voice |
Akhil Vijayan,
Anoop Ambika |
source
presentation source |
8 |
| PHUSE EU |
2018 |
Can You Cut It? Implementing the Data Cut-off |
Lewis Meares |
source
presentation source |
9 |
| PHUSE EU |
2018 |
CDISC SDTM Data Automation Tool |
Brinitha Sathyabhama |
source
presentation source |
6 |
| PHUSE EU |
2018 |
Data Mapping using Machine Learning |
Daniel Choi |
source
poster source |
3 |
| PHUSE EU |
2018 |
Data Transparency - Breaking Down Data Silos for Improved Insight |
Peter Tormay,
Anna Berg |
source
presentation source |
8 |
| PHUSE EU |
2018 |
Do's and Don'ts of Define.xml |
David Roulstone |
source
presentation source |
10 |
| PHUSE EU |
2018 |
eSource to SDTM: Trade-offs and Pay-offs |
Donald Benoot,
Swapna Pothula |
source
presentation source |
11 |
| PHUSE EU |
2018 |
How Machine Learning Can Automate Data Standardization in Clinical Trials [presentation] |
Fanyi Zhang |
source |
16 |
| PHUSE EU |
2018 |
Implementation of Data Cut Off in Analysis of Clinical Trials |
Ann Croft |
source
presentation source |
13 |
| PHUSE EU |
2018 |
Optimizing the Traceability Method in ADaM Parallel Conversions |
Roxane Debrus |
source
presentation source |
15 |
| PHUSE EU |
2018 |
Please Put Your Data in an Upright Position - Or How to Tackle Verticalisation |
Kristina Zweier |
source
presentation source |
9 |
| 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 |
Stop Copying CDISC Standards |
Craig Parry |
source
poster source |
21 |
| PHUSE EU |
2018 |
The interpretation and development of SDTM standards for non-submission purposes |
Paul Vervuren |
source
presentation source |
11 |
| PHUSE EU |
2018 |
Use of HL7 FHIR as eSource to Pre-populate CDASH Case Report Forms Using a CDISC ODM API |
Samuel Hume,
Geoff Low |
source
presentation source |
12 |
| SESUG |
2018 |
Data Integration Best Practices |
Harry Droogendyk |
source |
17 |
| SESUG |
2018 |
Hardcoding In Clinical Trials: A (Sometimes) Necessary Evil |
Gregory Weller |
source |
5 |
| MWSUG |
2018 |
Avoiding Sinkholes: Common Mistakes During ADaM Data Set Implementation |
Richann J. Watson |
|
15 |
| MWSUG |
2018 |
Seeing the Forest for the Trees: Part Deux of Defensive Coding by Example |
Donna E. Levy,
Nancy Brucken |
|
10 |
| WUSS |
2018 |
CDISC in Phase I/II Studies: Approaches to adopting standards for CSR deliverables |
Emily Woolley,
Amber Randall |
source |
9 |
| WUSS |
2018 |
Introduction to DATA Step Programming: SAS Basics II [presentation] |
Susan J. Slaughter |
source |
40 |
| WUSS |
2018 |
Parallel Processing with Base SAS |
Jim Barbour |
source |
17 |
| PHUSE US |
2018 |
ADaM Intermediate Dataset: How to Improve Your Analysis Traceability |
Angelo Tinazzi,
Ashish Aggarwal |
source
presentation source |
12 |
| 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 |
Challenges and Opportunities for Real-time Clinical Data Review [poster] |
Renu Shukla |
source |
1 |
| PHUSE US |
2018 |
Generating Table Listings and Figures Without Any Programs |
Shafi Chowdhury,
Md Zobair |
source
presentation source |
5 |
| PHUSE US |
2018 |
How do I have ONE Interpretation of CDISC for all my Studies? |
Mor Meyerovich |
source
presentation source |
5 |
| PHUSE US |
2018 |
It's Time To Change |
David Iberson-Hurst |
source |
14 |
| 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 |
Optimizing SDTM Specification Development with Auto-population |
Cori Kramer,
Ryan Adalbert |
source
presentation source |
6 |
| PHUSE US |
2018 |
Supporting a Data Review and Visualization Application with SDTM |
Deepika Sunkara,
Jagadish Dhanraj |
source
presentation source |
6 |
| PHUSE US |
2018 |
Transforming Clinical Trials with Linked Data |
Tim P. Williams,
Armando Oliva |
source
presentation source |
9 |
| PHUSE US |
2018 |
Use of HL7 FHIR as eSource to Pre-populate CDASH Case Report Forms Using a CDISC ODM API |
Samuel Hume,
Geoff Low |
source
presentation source |
12 |
| PharmaSUG |
2018 |
A CRO's perspective on successful partnering to deliver SDTM/SEND contributions |
Helen Owen,
Kirsty Payne |
source |
7 |
| PharmaSUG |
2018 |
ADaM Structures for Integration: A Preview |
Deborah J. Bauer,
Kimberly Minkalis,
Wayne Zhong |
source |
14 |
| PharmaSUG |
2018 |
Avoiding Sinkholes: Common Mistakes During ADaM Data Set Implementation |
Richann J. Watson,
Karl Miller |
source |
18 |
| PharmaSUG |
2018 |
Best Practices in Data Standards Governance |
Melissa R. Martinez |
source |
4 |
| PharmaSUG |
2018 |
Building Simulated CRF Data for Study Mock-Ups |
Ashley Kesler,
Hisham Madi,
Jonathan W. Duggins,
James E. Blum |
source |
10 |
| PharmaSUG |
2018 |
Challenges & Strategies in PKPD Programming |
Jing Su,
Jiannan Kang |
source |
6 |
| PharmaSUG |
2018 |
Challenges in Implementing Device Related ADaM and SDTM Standards in a Drug-Device Study |
Wenying Tian,
Maureen Maunsell,
Karin LaPann |
source |
9 |
| PharmaSUG |
2018 |
Common Data Related Review Issues and Prevention: A Statistical Reviewer's Thoughts |
Huanyu Chen |
source |
18 |
| PharmaSUG |
2018 |
Creating an ADaM Data Set for Correlation Analyses |
Chad W. Melson |
source |
11 |
| PharmaSUG |
2018 |
Data Standards for Population Pharmacokinetic (POPPK) and Non-Compartmental Analysis (NCA) |
Neelima Thanneer |
source |
7 |
| PharmaSUG |
2018 |
Designing Flexible Data Standards Models |
Melissa R. Martinez |
source |
4 |
| PharmaSUG |
2018 |
Dosing In NONMEM Datasets an Enigma |
Sree Harsha Sreerama Reddy,
Vishak Subramoney |
source |
11 |
| PharmaSUG |
2018 |
Implementation of Data Cut Off in Analysis of Clinical Trials |
Mei Dey |
source |
15 |
| PharmaSUG |
2018 |
Let's get to the Source and streamline it to the End |
Jennifer Price |
source |
6 |
| PharmaSUG |
2018 |
Macro-Supported Metadata-Driven Process for Mapping SDTM VISIT and VISITNUM |
Pragathi Dayananda,
Eric Crockett |
source |
6 |
| PharmaSUG |
2018 |
Preparing to Meet FDA Requirements for Submission of Standardized Data and Documentation |
Steven R. Kirby,
Mario Widel |
source |
11 |
| PharmaSUG |
2018 |
Proactive Role of a Lead Programmer Could Help Prevent Potential Delay in Submission |
Charan Vem,
Ranjith Kalleda |
source |
4 |
| PharmaSUG |
2018 |
Regulatory Compliance in the digital age - A cloud-based statistical computing environment (SCE) to the rescue |
Sridhar Vijendra,
Tyagrajan Swaminathan |
source |
9 |
| PharmaSUG |
2018 |
Seeing the Forest for the Trees: Part Deux of Defensive Coding by Example |
Donna E. Levy,
Nancy Brucken |
source |
10 |
| PharmaSUG |
2018 |
Statistical Programming: Revolution, Evolution, or Status Quo? |
Jeffrey M. Abolafia,
Frank C. DiIorio |
source |
9 |
| PharmaSUG |
2018 |
The Changing Clinical Data Analytics Landscape - Visualization & Beyond |
Siddartha Kondapally,
Kishore Pothuri,
Bhavin Busa |
source |
6 |
| PharmaSUG |
2018 |
Tips and Fixes for Cross-Environment Batch Transfer of SAS Data |
Yun (Julie) Zhuo |
source |
10 |
| PharmaSUG |
2018 |
UTF What? A Guide for Handling SAS Transcoding Errors with UTF-8 Encoded Data |
Michael Stackhouse,
Lavanya Pogula |
source |
15 |
| PharmaSUG |
2018 |
Want Submission-Ready Datasets Package from the Get-Go? |
Kishore Pothuri,
Bhavin Busa |
source |
8 |
| PharmaSUG |
2018 |
Watch Out For Blind Spots While Keeping Up With the Speed of Evolving Standards and Regulations |
Srinivas Veeragoni |
source |
14 |
| PharmaSUG |
2018 |
Why choose between DATA Step or PROC SQL when you can have both? |
Charu Shankar |
source |
5 |
| SGF |
2018 |
Data Integration Best Practices |
Harry Droogendyk |
source |
17 |
| SGF |
2018 |
Enterprise, Prepare for Analysis! Using SAS Data Management to Prepare Data for Analysis |
Bob Janka |
source |
17 |
| SGF |
2018 |
How Statistically Analyzing System Behaviors with SAS Visual Analytics Revealed Unknown Data Issues |
Jessica Fraley |
source |
8 |
| SGF |
2018 |
Implementing Privacy Protection-Compliant SAS Aggregate Reports |
Leonid Batkhan |
source |
14 |
| SGF |
2018 |
Just Enough SAS Cloud Analytic Services: CAS Actions for SAS Visual Analytics Report Developers |
Michael Drutar |
source |
14 |
| SGF |
2018 |
Macro Method to use Google Maps and SAS to Geocode a Location by Name or Address |
Laurie Smith |
source |
8 |
| SGF |
2018 |
Navigating the Analytics Life Cycle with SAS Visual Data Mining and Machine Learning |
Susan Haller,
Brett Wujek |
source |
29 |
| SGF |
2018 |
Run-Time Validation of SAS Jobs: A Threesome of Error-Throwing Macros |
Quentin McMullen |
source |
18 |
| SGF |
2018 |
Seeing the Forest for the Trees: Part Deux of Defensive Coding by Example |
Nancy Brucken,
Donna E. Levy |
source |
10 |
| SGF |
2018 |
Shorter Waiting Time, Better Emergency Healthcare: Forecasting Stockholms' Emergency Room Visits |
Martin Nordberg,
Oskar Eriksson |
source |
24 |
| SGF |
2018 |
So Many Date Formats: Which Should You Use? |
Kamleshkumar Patel |
source |
6 |
| SESUG |
2017 |
An Introduction to Visit Window Challenges and Solutions |
Mai Ngo |
source |
6 |
| SESUG |
2017 |
Challenges and Solutions for Handling Re - screened Subjects in SDTM |
Charity Quick,
Paul Nguyen |
source |
6 |
| SESUG |
2017 |
Churn the Data Around - A Machine Learning Approach to Understanding Why Customers Leave |
Sean Ankenbruck |
source |
9 |
| SESUG |
2017 |
Detecting Outlying Data in Proficiency Studies with SAS |
Stacey Slone |
source |
11 |
| SESUG |
2017 |
Dynamically Assigning Length to Transposed Variables |
Ethan Ritchie |
source |
5 |
| SESUG |
2017 |
Statistician's secret weapon: 20 ways of detecting raw data issues |
Lixiang Larry Liu |
source |
8 |
| SESUG |
2017 |
Streamlining ADaM Dataset Specifications |
Hunter Vega |
source |
6 |
| SESUG |
2017 |
When ANY Function Will Just NOT Do |
Richann J. Watson |
source |
8 |
| SCSUG |
2017 |
Don't Fear The Network: Beat A Slow Network With Data Content Maps |
Michael McCarthy |
source |
12 |
| SCSUG |
2017 |
The Good, The Bad, and The Ugly |
Toby Dunn,
Kirk Paul Lafler |
source |
12 |
| PHUSE EU |
2017 |
An FDA Submission Experience Using the CDISC Standards |
Angelo Tinazzi,
Cédric Marchand |
source
presentation source |
15 |
| PHUSE EU |
2017 |
Applying the OMOPCommon Data Model to Dutch Healthcare Data: A Case Study |
Rients van Wijngaarden |
source
presentation source |
5 |
| PHUSE EU |
2017 |
Are you Still Afraid of Using Arrays? Let's Explore their Advantages |
Vladyslav Khudov |
source
presentation source |
6 |
| PHUSE EU |
2017 |
Completing the Data Set Jigsaw: Hints and Tips for Assembling Data Sets Together |
Cerys Rand |
source
presentation source |
9 |
| PHUSE EU |
2017 |
Consuming Your Metadata for a Healthy Mapping |
Alan Cantrell,
Julius Kusserow |
source
presentation source |
4 |
| PHUSE EU |
2017 |
Devices Big Data and Real World Evidence |
Mike Collinson |
source
presentation source |
7 |
| PHUSE EU |
2017 |
GUI Method of Mapping SDTM from Raw Data |
Elisa Natale |
source
presentation source |
7 |
| PHUSE EU |
2017 |
Harmonizing SDTM at the Source: Designing Collection Instruments that Support Sponsor Standards |
Sue Huxtable,
Charlotte Lomberg |
source
presentation source |
7 |
| PHUSE EU |
2017 |
Presenting Study Results form a Metadata-driven Ecosystem |
Rajwanur Rahman |
source
presentation source |
6 |
| PHUSE EU |
2017 |
Putting Sisyphus Out of a Job, Making Health Care Research a Reality [presentation] |
Geoff Low |
source |
26 |
| PHUSE EU |
2017 |
REACTing to Data: The Use of Data Visualisation within Early Clinical StatisticalProgramming at AstraZeneca |
Shyamprasad Perisetla,
Suzanne Tautz |
source
presentation source |
6 |
| PHUSE EU |
2017 |
Worst CDISC Implementation Processes - How to Avoid Some Very Basic Mistakes in SDTM ADaM Define |
Hannes Engberg Reader,
Michale Riech |
source
presentation source |
10 |
| MWSUG |
2017 |
An Array of Possibilities: Manipulating Longitudinal Survey Data with Arrays |
Lakhpreet Gill |
|
8 |
| WUSS |
2017 |
Avoiding Sinkholes: Common Mistakes During ADaM Data Set Implementation |
Richann J. Watson,
Karl Miller |
source |
15 |
| WUSS |
2017 |
Introduction to DATA Step Programming: SAS Basics II |
Susan J. Slaughter |
|
39 |
| PharmaSUG CN |
2017 |
Overview of OSI Deliverables from Programming Perspective |
Wang Zhang |
|
6 |
| PharmaSUG |
2017 |
A SASsy Study of eDiary Data |
Amie Bissonett |
source |
5 |
| PharmaSUG |
2017 |
Building a Fast Track for CDISC: Practical Ways to Support Consistent, Fast and Efficient SDTM Delivery |
Steven R. Kirby,
Mario Widel,
Richard Addy |
source |
14 |
| PharmaSUG |
2017 |
Clinical and Vendor Database Harmony; Can-t we all just get along? |
Brian Armstrong,
Renee Kerwin |
source |
9 |
| PharmaSUG |
2017 |
Dear Dave, Please See the .LST File for Our Validation Differences. Thanks, Bad Validation Programmer |
Tracy Sherman,
David W. Carr,
Brian P. Fairfield-Carter |
source |
9 |
| PharmaSUG |
2017 |
LBTEST/LBSTRESU and ADaM lab parameters: The dilemma of mapping one-to-many or many-to-one |
Michelle Barrick |
source |
5 |
| PharmaSUG |
2017 |
Leveraging metadata when mapping to CDISC Standards with SAS machine learning in a Results as a Service plus Model (RAAS+) |
Ben E. Bocchicchio,
Sandeep Juneja,
Preetesh Parikh |
source |
6 |
| PharmaSUG |
2017 |
Leveraging Study Data Reviewer-s Guide (SDRG) in Building FDA-s Confidence in Sponsor-s Submitted Datasets |
Xiangchen (Bob) Cui,
Min Chen,
Letan (Cleo) Lin |
source |
10 |
| PharmaSUG |
2017 |
Programming Efficiency in the Creation of ADaM BDS Datasets |
Ellen (Zihui) Lin |
source |
11 |
| PharmaSUG |
2017 |
Statistician's secret weapon: 20 ways of detecting raw data issues |
Lixiang Larry Liu |
source |
8 |
| PharmaSUG |
2017 |
Use of Traceability Chains in Study Data and Metadata for Regulatory Electronic Submission |
Tianshu Li |
source |
8 |
| SGF |
2017 |
A Big-Data Challenge: Visualizing Social Media Trends about Cancer Using SAS Text Miner |
Scott Koval,
Yijie Li,
Mia Lyst |
source |
8 |
| SGF |
2017 |
Automate Validation of CDISC SDTM with SAS |
Sy J. Truong |
source |
11 |
| SGF |
2017 |
Automatically Map CDASH Data to the Study Data Tabulation Model (SDTM) Structure |
Hao Xu,
Hong Chen |
source |
18 |
| SGF |
2017 |
Circular Metadata Group Membership Can Make Us Dizzy! |
Karen Hinkson,
Greg Lehner |
source |
22 |
| SGF |
2017 |
Going Green With Your SAS Applications |
Michael A. Raithel |
source |
17 |
| SGF |
2017 |
Investigating Big-Data Crime Scenes |
Theresa H. Ngo |
source |
10 |
| SGF |
2017 |
J2SP: An Investigation in Social Factors That Might Influence National GDP |
John Eacott,
Parselvan Aravazhi,
Sid Grover,
Jayant Sharma |
source |
16 |
| SGF |
2017 |
More Than Just a Pretty Face: Using SAS Output Delivery System to Create Microsoft Excel Worksheets That Answer Those Difficult Questions |
Chevell T. Parker |
source |
27 |
| SGF |
2017 |
Nine Best Practices for Big Data Dashboards Using SAS Visual Analytics |
Elena Snavely |
source |
7 |
| SGF |
2017 |
Quality Control Programming: A Lost Art? |
Amber Randall,
Bill Coar |
source |
15 |
| SGF |
2017 |
Random Forests with Approximate Bayesian Model Averaging |
Tiny Du Toit,
Andre De Waal |
source |
11 |
| SGF |
2017 |
So You Think You Can Combine Data Sets? |
Christopher J. Bost |
source |
23 |
| SGF |
2017 |
When ANY Function Will Just NOT Do |
Richann J. Watson,
Karl Miller |
source
pdf |
8 |
| PHUSE EU |
2016 |
A Standardised Approach to De-identification |
Christopher C. Hurley |
source
presentation source |
13 |
| PHUSE EU |
2016 |
Constructing a Clinical Data Warehouse for Nutrition Studies [presentation] |
Paul Vervuren |
source |
27 |
| PHUSE EU |
2016 |
DIY: Create Your Own SDTM Mapping Framework |
Bas van Bakel |
source
presentation source |
11 |
| PHUSE EU |
2016 |
Efficiency comes From Reusability and Repeatability |
Hanming Tu,
Dave Evans |
source
presentation source |
10 |
| PHUSE EU |
2016 |
Get Kitted Out - A Practical Guide to SAS Certifications, MOOCs and Hands-on Experience |
Hannes Engberg Raeder |
source |
6 |
| PHUSE EU |
2016 |
Grading Lab Toxicities using NCI Common Terminology Criteria for Adverse Events (CTCAE) |
Srinivas Veeragoni,
Ankur Mathur |
source
presentation source |
10 |
| 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 |
Keeping Track of Database Changes During Database Lock |
Sanjiv Ramalingam |
source
presentation source |
6 |
| 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 |
Program-level Programming Strategy - Oh, I Wish I'd Thought of That Beforehand! |
Jennie McGuirk |
source
presentation source |
9 |
| PHUSE EU |
2016 |
QC of the aCRF Using SAS |
Rune Pedersen,
Niels Both |
source
presentation source |
12 |
| PHUSE EU |
2016 |
The Data Detective: Hints and Tips for Independent Programming QC |
Bethan Thomas |
source |
11 |
| PHUSE EU |
2016 |
Using Graphics to Review and Present PK/PD Data for Maximum Impact |
Shafi Chowdhury,
Rajwanur Rahman |
source |
9 |
| MWSUG |
2016 |
Defensive Coding by Example: Kick the Tires, Pump the Brakes, Check Your Blind Spots, and Merge Ahead! |
Nancy Brucken,
Donna E. Levy |
|
16 |
| MWSUG |
2016 |
Your Place or Mine: Data-Driven Summary Statistic Precision |
Nancy Brucken |
|
4 |
| PharmaSUG CN |
2016 |
PPG, a metadata driven solution for patient profile generation |
Weina Jia,
Eric Li,
Vincent Fan,
Yihong Chi,
Qingan Chang |
|
5 |
| WUSS |
2016 |
You are the Concierge - a CDISC compliant project management tool on SDD |
Chen Shi |
source |
1 |
| 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 |
Data Visualization for Quality Control in NONMEM Data set |
Linghui Zhang |
source |
9 |
| PharmaSUG |
2016 |
Moving from Data Collection to Data Visualization and Analytics: Leveraging CDISC SDTM Standards to Support Data Marts |
Steven R. Kirby,
Terek Peterson |
source |
8 |
| PharmaSUG |
2016 |
Prepare for Re-entry: Challenges and Solutions for Handling Re-screened Subjects in SDTM |
Charity Quick,
Paul Nguyen |
source |
5 |
| PharmaSUG |
2016 |
Preparing Legacy Format Data for Submission to the FDA - When & Why Must I Do It, What Guidance Should I Follow? |
David C. Izard |
source |
11 |
| PharmaSUG |
2016 |
Quick and Efficient Way to Check the Transferred Data |
Divyaja Padamati |
source |
6 |
| PharmaSUG |
2016 |
SDTM Automation with Standard CRF Pages |
Taylor Markway |
source |
10 |
| PharmaSUG |
2016 |
Strategic Considerations for CDISC Implementation |
Amber Randall,
William Coar |
source |
6 |
| PharmaSUG |
2016 |
The Devil is in the Details - Reporting from Pinnacle 21 (OpenCDISC) Validation Report |
Amy Garrett,
Chris Whalen |
source |
11 |
| PharmaSUG |
2016 |
UTF What? A Guide to Using UTF-8 Encoded Data in a SDTM Submission |
Michael Stackhouse |
source |
10 |
| PharmaSUG |
2016 |
Validation Methods and Strategies for Presentation of Clinical Reports: The Programmers Road Map to Success |
Vijayata Sanghvi |
source |
5 |
| PharmaSUG |
2016 |
When ANY Function Will Just NOT Do |
Richann J. Watson,
Karl Miller |
source |
8 |
| SGF |
2016 |
Agile BI: How Eandis is using SAS Visual Analytics for Energy Grid Management |
Olivier Goethals |
source |
8 |
| SGF |
2016 |
An End-to-End, Automation Framework for Implementing Identity-Driven Row-Level Security Using SAS Visual Analytics |
Paul W. Johnson,
Ekaitz Goienola,
Dileep Pournami |
source |
12 |
| SGF |
2016 |
Architecting Data Management: Seven Principles Using SAS, DataFlux, and SQL |
Bob Janka |
source |
20 |
| SGF |
2016 |
Can You Read This into SAS for Me? Using INFILE and INPUT to Load Data into SAS |
Peter W. Eberhardt,
Audrey Yeo |
source |
20 |
| SGF |
2016 |
Case Study: SAS Visual Analytics Dashboard for Pollution Analysis |
Viraj R Kumbhakarna |
source |
12 |
| SGF |
2016 |
Releasing the Power of SAS into Microsoft SharePoint |
Xiaogang Tang |
source
zip |
8 |
| SGF |
2016 |
Using SAS Arrays to Calculate Bouts of Moderate to Vigorous Physical Activity from Minute-by-Minute Fitbit Data |
Faith Parsons,
Keith M Diaz,
Jacob E Julian |
source
zip |
13 |
| MWSUG |
2015 |
Base SAS Sentiment Analysis Using Catchprases |
Mike D. Tangedal |
|
9 |
| MWSUG |
2015 |
You Can't Spell 'Assume' without S.A.S. |
Mike D. Tangedal |
|
8 |
| 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 |
Constructing a Simple Data Repository [presentation] |
Magnus Mengelbier |
source |
19 |
| PHUSE EU |
2015 |
Data-centric System Development Life Cycle for Automated Clinical Data Development Systems |
Kevin Lee |
source
presentation source |
5 |
| 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 |
Implementation of an in-house Data QC Tool to Streamline SDTM Production Data |
Karlien Knevels |
source
presentation source |
3 |
| 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 |
Metadata Snapshots: How SAS Drug Development API Macros Can Help |
Melissa R. Martinez |
source
presentation source |
12 |
| PHUSE EU |
2015 |
Programming Strategically for PK/PD Data |
Grace Lu |
source
presentation source |
8 |
| PHUSE EU |
2015 |
Using Graphics to Present the Study Result as a Story |
Shafi Chowdhury,
Rajwanur Rahmann |
source
presentation source |
10 |
| PHUSE EU |
2015 |
WPP, Worst Programming Practice - Real-life Pittfalls in Everyday Clinical Programming: Why and How |
Hannes Engberg Raeder,
Rowland Hale |
source
presentation source |
14 |
| SESUG |
2015 |
A Methodology for Truly Dynamic Prompting in SAS Stored Processes |
Haikuo Bian,
David Maddox |
source |
12 |
| SESUG |
2015 |
Documentation as You Go: aka Dropping Breadcrumbs! |
Elizabeth Axelrod |
source |
4 |
| SESUG |
2015 |
Having a Mean Headache on Summary Data? Using SAS to Compute Actual Data from Summary Data |
William 'Gui' Zupko II |
source |
4 |
| WUSS |
2015 |
Architecting Data Management: 7 Principles using SAS, DataFlux and SQL |
Bob Janka |
source |
17 |
| WUSS |
2015 |
Exploring SAS Visual Analytics capabilities to go from Fat to Fit! |
Viraj R Kumbhakarna |
source |
22 |
| WUSS |
2015 |
Getting Loopy with SAS DICTIONARY Tables: Using Metadata from DICTIONARY Tables to Fulfill Submission Requirements |
Jeanina M. Worden |
source |
8 |
| WUSS |
2015 |
SAS Certification as a Tool for Professional Development |
Susan J. Slaughter,
Andra Northup |
source |
17 |
| PharmaSUG CN |
2015 |
Generating Define.xml Using SAS By Element-by-Element And Domain-by-Domian Mechanism |
Lina Qin |
|
12 |
| PharmaSUG CN |
2015 |
How to validate clinical data more efficiently with SAS Clinical Standards Toolkit |
Vivian Feng |
|
11 |
| PharmaSUG CN |
2015 |
Statistics And Programming In The Globally Evolving Landscape Of Clinical Trial Registration And Results (CTRR) Disclosure |
Paul Ngai,
Joyce Hauze |
|
8 |
| PharmaSUG CN |
2015 |
Summary level clinical site data for data integrity review and inspection planning in NDA and BLA submission [presentation] |
Jingwei Gao,
Nancy Bauer |
|
41 |
| PharmaSUG CN |
2015 |
Tips for efficient CDISC eCRT production |
Lanting Li,
Yu Zhu,
Yuejuan Meng,
Huan Zhu |
|
11 |
| PharmaSUG |
2015 |
Begin with the End in Mind - Using FDA Guidance Documents as Guideposts when Planning, Delivering and Archiving Clinical Trials |
David C. Izard |
source |
12 |
| PharmaSUG |
2015 |
Challenges in Developing ADSL with Baseline Data |
Hongyu Liu,
Hang Pang |
source |
6 |
| PharmaSUG |
2015 |
Defensive Coding by Example: Kick the Tires, Pump the Breaks, Check Your Blind Spots, and Merge Ahead! |
Nancy Brucken,
Donna E. Levy |
source |
16 |
| PharmaSUG |
2015 |
Evaluating SDTM SUPP Domain For AdaM - Trash Can Or Buried Treasure |
Xiaopeng Li,
Yi Liu,
Chun Feng |
source |
7 |
| PharmaSUG |
2015 |
Getting Loopy with SAS DICTIONARY Tables: Using Metadata from DICTIONARY Tables to Fulfill Submission Requirements |
Jeanina M. Worden |
source |
8 |
| PharmaSUG |
2015 |
Growing Needs in Drug Industry for NONMEM Programmers Using SAS |
Sharmeen Reza |
source |
11 |
| PharmaSUG |
2015 |
Leveraging ADaM Principles to Make Analysis Database and Table Programming More Efficient |
Andrew L Hulme |
source |
13 |
| PharmaSUG |
2015 |
Managing Custom Data Standards in SAS Clinical Data Integration |
Melissa R. Martinez |
source |
17 |
| PharmaSUG |
2015 |
R you ready to show me Shiny for PharmaSUG 2015 |
Amulya R. Bista,
Jeff Cai |
source |
5 |
| PharmaSUG |
2015 |
Subset without Upsets: Concepts and Techniques to Subset SDTM Data |
Jhelum Naik,
Sajeet Pavate |
source |
6 |
| PharmaSUG |
2015 |
Team-work and Forensic Programming: Essential Foundations of Indestructible Projects |
Brian P. Fairfield-Carter |
source |
14 |
| SGF |
2015 |
Can You Read This into SAS for Me? Using INFILE and INPUT to Load Data into SAS |
Peter W. Eberhardt,
Audrey Yeo |
source |
20 |
| SGF |
2015 |
Defensive Coding by Example: Kick the Tires, Pump the Breaks, Check Your Blind Spots, and Merge Ahead! |
Donna E. Levy,
Nancy Brucken |
source |
17 |
| SGF |
2015 |
Documentation as You Go: aka Dropping Breadcrumbs! [presentation] |
Elizabeth Axelrod |
source |
4 |
| SGF |
2015 |
How Best to Effectively Teach the SAS Language |
Arthur X. Li |
source |
13 |
| SGF |
2015 |
Lasso Your Business Users by Designing Information Pathways to Optimize Standardized Reporting in SAS Visual Analytics |
Stephen M. Overton |
source |
15 |
| SGF |
2015 |
Master Data and Command Results: Combine Master Data Management with SAS Analytics for Improved Insights |
Ron Agresta |
source |
6 |
| SGF |
2015 |
Performing Efficient Transposes on Large Teradata Tables Using SQL Explicit Pass-Through |
Tao Cheng |
source |
17 |
| SGF |
2015 |
PROC SQL for PROC SUMMARY Stalwarts |
Christianna S. Williams |
source |
19 |
| SGF |
2015 |
SAS Certification as a Tool for Professional Development |
Andra Northup,
Susan J. Slaughter |
source |
17 |
| SGF |
2015 |
SAS Data Management: Technology Options for Ensuring a Quality Journey Through the Data Management Process |
Mark Craver |
source |
12 |
| SGF |
2015 |
SAS Visual Analytics for Fun and Profit: A College Football Case Study |
John Davis |
source |
18 |
| SGF |
2015 |
Using SAS to Deliver Web Content Personalization Using Cloud-Based Clickstream Data and On-premises Customer Data |
Mahesh Subramanian,
Suneel Grover |
source |
24 |
| SGF |
2015 |
Visualizing Relationships and Connections in Complex Data Using Network Diagrams in SAS Visual Analytics |
Stephen Overton,
Ben Zenick |
source
zip |
15 |
| SGF |
2015 |
Want an Early Picture of the Data Quality Status of Your Analysis Data? SAS Visual Analytics Shows You How |
Gerhard Svolba |
source
zip |
19 |
| SESUG |
2014 |
Evaluating Additivity of Health Effects of Exposure to Multiple Air Pollutants Given Only Summary Data |
Pollutants Given |
source |
9 |
| SESUG |
2014 |
PROC SQL for PROC SUMMARY Stalwarts |
Christianna S. Williams |
source |
18 |
| SESUG |
2014 |
Secure SAS OLAP Cubes with Top-Secret Permissions |
Stephen M. Overton |
source |
11 |
| SESUG |
2014 |
The Power of PROC APPEND |
Ted Logothetti |
source |
7 |
| 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 |
Looking for SDTM Migration Specialist |
Angelo Tinazzi |
source
presentation source |
12 |
| PHUSE EU |
2014 |
Risk based monitoring using integrated clinical development platform Authors |
Sita Rama Swamy Peddiboyina,
Shailesh Vijay Joshi |
source
presentation source |
9 |
| PHUSE EU |
2014 |
SDTM Mapping Becomes more EASY with SAS Clinical Data Integration |
Saumilkumar Tripathi |
source
presentation source |
8 |
| PHUSE EU |
2014 |
Study Data Handling: A CRO Experience |
Paul Crean |
source
presentation source |
6 |
| PHUSE EU |
2014 |
Submitting Summary Level Site Data: Overview, Implementation and Case Studies |
Robert F. Woolson,
Jeffrey M. Abolafia,
Ben Vaughn |
source
presentation source |
9 |
| MWSUG |
2014 |
So You Want to be SAS Certified |
Ben Cochran |
|
10 |
| MWSUG |
2014 |
The Armchair Quarterback: Writing SAS Code for the Perfect Pivot (Table, That Is) |
Peter W. Eberhardt |
|
36 |
| MWSUG |
2014 |
Understanding How the DATA Step Works |
Arthur X. Li |
|
13 |
| PharmaSUG CN |
2014 |
Submission of Pharmacokinetics (PK) Data in a CDISC Compliant Format |
Yu Zhu |
|
9 |
| PharmaSUG CN |
2014 |
The Power of SAS National Language Support - Embrace Multilingual Data |
Chao Wang |
|
10 |
| WUSS |
2014 |
How can I simplify ETL when I only have Base SAS |
Steve Cavill |
source |
15 |
| WUSS |
2014 |
Reanalysis of Ecological Data from the 1989 China Study Using SAS Enterprise Guide |
Thomas E. Billings |
source |
17 |
| WUSS |
2014 |
SAS Certification as a Tool for Professional Development |
Andra Northup,
Susan J. Slaughter |
source |
11 |
| WUSS |
2014 |
You Say 'Day-ta', I Say 'Dat-a' - Processing Your DATA Efficiently and Ensuring Its Integrity |
Mary Federico Katz,
Jason R. Beene |
source |
12 |
| PharmaSUG |
2014 |
A Shout-out to Specification Review: Techniques for an efficient review of Programming Specifications |
Sajeet Pavate,
Jhelum Naik |
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 |
Create Excel TFLs Using the SAS Add-in |
Jeffrey Tsao,
Tony Chang |
source |
6 |
| PharmaSUG |
2014 |
SAS as a Tool to Manage Growing SDTM+ Repository for Medical Device Studies |
Julia Yang |
source |
12 |
| PharmaSUG |
2014 |
That SASsy Lab Data |
Amie Bissonett |
source |
6 |
| PharmaSUG |
2014 |
Validating Analysis Data Set without Double Programming - An Alternative Way to Validate the Analysis Data Set |
Linfeng Xu,
Christina Scienski |
source |
15 |
| SGF |
2014 |
A Paradigm Shift: Complex Data Manipulations with DS2 and In-Memory Data Structures |
Shaun Kaufmann |
source |
10 |
| SGF |
2014 |
Automatic and Efficient Post-Campaign Analyses By Using SAS Macro Programs |
Justin Jia,
Amanda Lin |
source |
12 |
| 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 |
Conditional Execution "Switch Path" Logic in SAS Data Integration Studio 4.6 |
Prajwal Shetty |
source |
15 |
| SGF |
2014 |
Effective Risk Aggregation and Reporting Using SAS |
Wei Chen,
Jimmy Skoglund,
Srinivasan Iyer |
source |
9 |
| SGF |
2014 |
From Traffic to Twitter--Exploring Networks with SAS Visual Analytics |
Falko Schulz,
Nascif Abousalh-Neto |
source |
32 |
| SGF |
2014 |
Healthcare Services Data Distribution, Transformation, and Model Fitting |
Dawit Mulugeta,
Jason Greenfield,
Tison Bolen,
Lisa Conley |
source |
22 |
| SGF |
2014 |
Money Basketball: Optimizing Basketball Player Selection Using SAS |
Sabah Sadiq,
Jing Zhao |
source |
9 |
| SGF |
2014 |
PROC TABULATE: Extending This Powerful Tool Beyond Its Limitations |
Justin Jia,
Amanda Lin |
source |
11 |
| SGF |
2014 |
Real-Time Market Monitoring using SAS BI Tools |
Amol Deshmukh,
Jeff McDonald |
source |
10 |
| SGF |
2014 |
Secure SAS OLAP Cubes with Top-Secret Permissions |
Stephen M. Overton |
source |
11 |
| 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 |
Text Mining Economic Topic Sentiment for Time Series Modeling |
Michael P. Dessauer,
Justin Kauhl |
source |
14 |
| SGF |
2014 |
The Armchair Quarterback: Writing SAS Code for the Perfect Pivot (Table, That Is) |
Peter W. Eberhardt |
source |
36 |
| SGF |
2014 |
Using SAS Graph Template Language with SAS 9.3 Updates to Visualize Data When There is Too Much Data to Visualize |
Perry Watts,
Nathaniel Derby |
source |
20 |
| SGF |
2014 |
Using SAS Stored Processes To Build a Calibration Tool [presentation] |
Anita Measey |
source |
41 |
| WUSS |
2013 |
Solve Complex Business Challenges by Leveraging Advanced OLAP Cube Techniques and MDX Programming |
Stephen M. Overton |
source |
14 |
| SCSUG |
2013 |
The Concepts and Practice of Analysis with SAS Enterprise Guide |
Christopher W. Schacherer |
source |
48 |
| SCSUG |
2013 |
The Good, The Bad, and The Ugly |
Toby Dunn,
Kirk Paul Lafler |
source |
12 |
| SESUG |
2013 |
Binning Bombs When You're Not a Bomb Maker: A Code-Free Methodology to Standardize, Categorize, and Denormalize Categorical Data |
Binning Bombs |
source |
26 |
| SESUG |
2013 |
From Raw Data to Beautiful Graph Using JSL |
Michael Hecht |
source |
27 |
| SESUG |
2013 |
Seamless Dynamic Web (and Smart Device!) Reporting with SAS |
Donald L Penix Jr. |
source |
9 |
| SESUG |
2013 |
The Armchair Quarterback: Writing SAS Code for the Perfect Pivot (Table, That Is) |
Peter W. Eberhardt |
source |
36 |
| PHUSE EU |
2013 |
Datacut Strategies: What, Why & How |
Hiren Naygandhi |
source
presentation source |
6 |
| PHUSE EU |
2013 |
Elephants and Storms - Using Big Data Techniques for Analysis of Large and Changing Datasets |
Geoff Low |
source
presentation source |
9 |
| PHUSE EU |
2013 |
Mission Possible: Your Assignment is to Validate Output for a Study |
Susan Fehrer Coulson |
source
presentation source |
7 |
| PHUSE EU |
2013 |
Standards for the Management of Clinical Trial Data, Why are they Needed, What is Needed? |
Isabelle Abousahl |
source
presentation source |
11 |
| MWSUG |
2013 |
Building a Better Bar Chart with SAS Graph Template Language |
Perry Watts |
|
22 |
| MWSUG |
2013 |
SAS Automation - From Password Protected Excel Raw Data To Professional-Looking PowerPoint Report |
Jeff Hao |
|
13 |
| MWSUG |
2013 |
Seamless Dynamic Web (and Smart Device!) Reporting with SAS |
Donald L Penix Jr. |
|
9 |
| NESUG |
2013 |
Pooling strategy for clinical data |
Abraham Yeh,
ShinRu Wang,
Xiaohong Zhang |
|
11 |
| NESUG |
2013 |
The ADaM Solutions to Non-endpoints Analyses |
Chengxin Li |
|
12 |
| PharmaSUG |
2013 |
Be a Dead Cert for a SAS Cert: How to prepare for the most important SAS Certifications in the Pharmaceutical Industry |
Hannes Engberg Raeder |
source |
10 |
| PharmaSUG |
2013 |
Clinical Reporting by Elements |
Magnus Mengelbier |
source |
9 |
| PharmaSUG |
2013 |
Effective Independent Validation: Tips to Improve the Independent Validation Process |
Daniel Butner,
Brandon Graham |
source |
6 |
| PharmaSUG |
2013 |
Essentials of PDV: Directing the Aim to Understanding the DATA Step! |
Arthur X. Li |
source |
12 |
| PharmaSUG |
2013 |
If 'standard code' is so great ... |
Brian P. Fairfield-Carter |
source |
12 |
| PharmaSUG |
2013 |
Let SAS Set Up and Track Your Project |
Tom Santopoli,
Wayne (Weizhen) Zhong |
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 |
SDTM Harmonization in the Absence of CDASH - A Modularized Approach to Domain Programming |
Annie S. Guo |
source |
12 |
| PharmaSUG |
2013 |
The Armchair Quarterback: Writing SAS Code for the Perfect Pivot (Table, That Is) |
Peter W. Eberhardt |
source |
36 |
| PharmaSUG |
2013 |
The SAS Data Step: Where Your Input Matters |
Peter W. Eberhardt |
source |
18 |
| PharmaSUG |
2013 |
Using the SAS Clinical Standards Toolkit 1.5 to Import CDISC ODM Files |
Lex Jansen |
source |
28 |
| SGF |
2013 |
A Day in the Life of Data: Part 4 - Graphics and Reporting |
Sanjay N. Matange |
source |
12 |
| SGF |
2013 |
Bringing Churn Modeling Straight to the Source: SAS and Teradata In-Database Model Development |
Jonathan Wexler,
Karl Krycha |
source |
9 |
| SGF |
2013 |
Converting Thousands of Variables from Character to Numeric: The One-Hour Fix |
Kamya Khanna,
Wen Song |
source |
6 |
| SGF |
2013 |
Data Mining of U.S. Patents: Research Trends of Major Technology Companies |
Ken Potter,
Robert N. Hatton |
source |
11 |
| SGF |
2013 |
Escape from Big Data Restrictions by Leveraging Advanced OLAP Cube Techniques |
Stephen M. Overton |
source |
14 |
| SGF |
2013 |
Essentials of the Program Data Vector (PDV): Directing the Aim to Understanding the DATA Step |
Arthur X. Li |
source |
12 |
| SGF |
2013 |
Grand Designs: Why It Pays to Think About Technical Architecture Design Before You Act |
Simon Williams |
source |
18 |
| SGF |
2013 |
Implementing CDISC, SDTM, and ADaM in a SAS Environment |
Pankaj Bhardwaj |
source
pdf |
4 |
| SGF |
2013 |
Resources for Getting the 2010 US Census Summary Files into SAS |
Rebecca Ottesen |
source |
5 |
| SGF |
2013 |
SAS Data Management Techniques: Cleaning and Transforming Data for Delivery of Analytic Data Sets |
Christopher W. Schacherer |
source |
38 |
| SGF |
2013 |
The Armchair Quarterback: Writing SAS Code for the Perfect Pivot (Table, That Is) |
Peter W. Eberhardt |
source |
36 |
| SGF |
2013 |
The Concepts and Practice of Analysis with SAS Enterprise Guide |
Christopher W. Schacherer |
source |
48 |
| SGF |
2013 |
Time Series Data: Anatomy of an ETL Project |
Leonard Polak |
source |
7 |
| SGF |
2013 |
Using the ADaM ADAE Structure for Non-AE Data |
Mario Widel,
Sandra Minjoe |
source |
13 |
| NESUG |
2012 |
Integrating SAS and Excel: An Overview and Comparison of Three Methods for Using SAS to Create and Access Data in Excel |
Nathan Clausen,
Edmond Cheng |
|
14 |
| NESUG |
2012 |
Interesting Technical Mini-Bytes of Base SAS - From DATA Step to Macros |
Airaha Chelvakkanthan Manickam |
|
13 |
| NESUG |
2012 |
Standardized Production Processes for One Routine Government Publication - Using SAS 9.2 to Produce Mortality Tables for the National Center for Health Statistics' Annual Report, "Health, United States" |
Mary Ann Bush,
Sheila Franco,
Li-Hui Chen,
Shilpa Bengeri |
|
10 |
| NESUG |
2012 |
Using Axes Options to Stretch the Limits of SAS/GRAPH Template Language |
Perry Watts |
|
20 |
| NESUG |
2012 |
Using SAS GTL with 9.3 Updates to Visualize Data When There is Too Much of it to Visualize |
Perry Watts,
Nathaniel Derby |
|
20 |
| SCSUG |
2012 |
SAS Data Management Techniques: Cleaning and Transforming Data for Delivery of Analytic Data Sets |
Christopher W. Schacherer |
source |
38 |
| SCSUG |
2012 |
The Good, The Bad, and The Ugly |
Toby Dunn,
Kirk Paul Lafler |
source |
12 |
| SCSUG |
2012 |
The SAS Data Step: Where Your Input Matters |
Peter W. Eberhardt |
source |
18 |
| PHUSE EU |
2012 |
"Bertha.sas" - User Friendly Ways to get Traceability |
Elena Glathe |
source
presentation source |
28 |
| PHUSE EU |
2012 |
An Introduction to SDTM, 298 Pages in 20 Minutes? |
Jennie McGuirk |
source
presentation source |
8 |
| PHUSE EU |
2012 |
Approaches to Creating ADaM Subject-Level Analysis Datasets (ADSL) for Integrated Analyses |
Thomas Clinch,
Nate Friemark |
source
presentation source |
6 |
| PHUSE EU |
2012 |
Pooling Clinical Data: Key Points and Pitfalls |
Florence Buchheitt |
source
presentation source |
8 |
| PHUSE EU |
2012 |
Understanding SAS...the SAS-sy Way! |
Amar Nayak |
source
poster source |
8 |
| PHUSE EU |
2012 |
Using Metadata to Integrate and Standardise Clinical Trial Data - the ICON Study Data Mapper |
Paul Crean,
Jennie McGuirk |
source
presentation source |
6 |
| SESUG |
2012 |
An Introduction to the Clinical Standards Toolkit |
Mike Molter |
source |
13 |
| SESUG |
2012 |
Lost in Space? Methodology for a Guided Drill-Through Analysis Out of the Wormhole |
Stephen M. Overton |
source |
12 |
| SESUG |
2012 |
Using Axes Options to Stretch the Limits of SAS/GRAPH Template Language |
Perry Watts,
>>>> |
source |
20 |
| MWSUG |
2012 |
Creating a SAS Frequency Data Set of Valid Categorical Variables for Export to Microsoft Excel or Access |
Neil Kamdar |
|
7 |
| MWSUG |
2012 |
SAS Data Management Techniques: Cleaning and Transforming Data for Delivery of Analytic Data Sets |
Christopher W. Schacherer |
|
38 |
| MWSUG |
2012 |
SAS Macro Tool to Find Source Data Sets Used in Programs |
Prasanna Murugesan,
Sushant Thakare |
|
11 |
| MWSUG |
2012 |
The Armchair Quarterback: Writing SAS Code for the Perfect Pivot (Table, That Is) |
Peter W. Eberhardt |
|
36 |
| MWSUG |
2012 |
The Good, The Bad, and The Ugly |
Toby Dunn,
Kirk Paul Lafler |
|
12 |
| MWSUG |
2012 |
The SAS Data Step: Where Your Input Matters |
Peter W. Eberhardt |
|
18 |
| WUSS |
2012 |
Biology research data cleaning technical |
Kai Yang |
source |
12 |
| WUSS |
2012 |
Composite Indices for Health Outcomes in Epidemiologic Studies: Multi-dimensional Coding Using SAS |
Nadia Chung,
Huiyan Ma,
Jenna Voutsinas,
Leslie Bernstein,
Sophia Wang,
James Lacey |
source |
7 |
| WUSS |
2012 |
Guide Users along Information Pathways and Surf through the Data |
Stephen M. Overton |
source |
12 |
| WUSS |
2012 |
SAS Programming Basics: Getting Your Data In and Understanding the Data Step |
Helen D. Carey |
source |
13 |
| WUSS |
2012 |
The SAS Data Step: Where Your Input Matters |
Peter W. Eberhardt,
Lucheng Shao |
source |
18 |
| PharmaSUG CN |
2012 |
The Armchair Quarterback: Writing SAS Code for the Perfect Pivot (Table, That Is) |
Peter W. Eberhardt,
Louanna Kong |
|
36 |
| PharmaSUG |
2012 |
7 Steps to Progression Free Survival Insights Using SAS |
Karen Walker |
source |
12 |
| PharmaSUG |
2012 |
An Introduction to the Clinical Standards Toolkit and Clinical Data Compliance Checking |
Mike Molter |
source |
14 |
| PharmaSUG |
2012 |
Arriving 'Normally' at t-test for a treatment combination |
Naina Pandurangi |
source |
7 |
| PharmaSUG |
2012 |
Creating Metadata Driven Macros to Gain Dynamism and Reduce Complexity in Macro Calls |
Fernando Enriquez |
source |
5 |
| PharmaSUG |
2012 |
Database Tectonics: Assessing Drift in Analysis Data |
Brian P. Fairfield-Carter,
Jasmin Fredette |
source |
10 |
| PharmaSUG |
2012 |
Interesting Technical Mini-Bytes of Base SAS - From DATA Step to Macros |
Airaha Chelvakkanthan Manickam |
source |
13 |
| 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 |
Scrambling of Un-Blinded Data without 'Scrambling Data Integrity'! |
Jaya Baviskar |
source |
8 |
| PharmaSUG |
2012 |
SDTM Domain Development on the Critical Path - Strategies for Success |
David C. Izard |
source |
5 |
| PharmaSUG |
2012 |
SDTM, ADaM and define.xml with OpenCDISC |
Matthew J. Becker |
source |
14 |
| PharmaSUG |
2012 |
The SAS Data Step: Where Your Input Matters |
Peter W. Eberhardt |
source |
18 |
| PharmaSUG |
2012 |
Transform Incoming Lab Data into SDTM LB Domain with Confidence |
Anthony L. Feliu |
source |
27 |
| SGF |
2012 |
10,000 Leagues of Data... Divide and Conquer OLAP Cubes: Best Practices for High Volumes of Data |
Stephen M. Overton |
source |
6 |
| SGF |
2012 |
Defining the Development Process and Governance of Implementing ADaM within an Organization |
Chris Decker |
source |
11 |
| SGF |
2012 |
Developing a Flexible ETL Process to Let SAS Capture Data Changes Efficiently in a Data Warehouse and Clean Up the Mess |
Stephen M. Overton |
source |
8 |
| SGF |
2012 |
Interesting Technical Mini-Bytes of Base SASFrom DATA Steps to Macros |
Airaha Chelvakkanthan Manickam |
source |
13 |
| SGF |
2012 |
Lost in Wonderland? Methodology for a Guided Drill-Through Analysis Out of the Rabbit Hole |
Stephen M. Overton |
source |
12 |
| SGF |
2012 |
SAS OLAP Cube Tuning and Query Performance Optimization |
Tatyana Petrova |
source |
17 |
| SGF |
2012 |
Sending E-mails in Your Sleep |
Andrew Hummel |
source |
5 |
| SGF |
2012 |
The Armchair Quarterback: Writing SAS Code for the Perfect Pivot (Table, That Is) |
Peter W. Eberhardt,
Louanna Kong |
source |
36 |
| SGF |
2012 |
The Good, The Bad, and The Ugly |
Toby Dunn,
Kirk Paul Lafler |
source |
12 |
| SGF |
2012 |
Using Pre-Formatted Microsoft Excel Templates with SAS |
George G. Mendoza,
Subhashree Singh |
source |
13 |
| SGF |
2012 |
Using SAS GTL to Visualize Your Data when there is Too Much of it to Visualize |
Perry Watts,
Nathaniel Derby |
source |
21 |
| SGF |
2012 |
Your Place or Mine: Data-Driven Summary Statistic Precision |
Nancy Brucken |
source |
4 |
| SCSUG |
2011 |
At Random - Sampling with PROC SURVEYSELECT |
Patricia Hettinger |
source |
15 |
| SCSUG |
2011 |
The easy way to include XML formatted data into your SAS reports |
Mary Grace Crissey |
source |
7 |
| SCSUG |
2011 |
You Can't Get There From Here If You Don't Know Where Here Is. Improving the SAS Enterprise Guide Data Characterization Task |
Patricia Hettinger |
source |
16 |
| SESUG |
2011 |
Using SAS to Streamline Periodic Reporting of Summary Statistics: Proc Format, Proc Freq, Proc Means,and Output Delivery System |
Berwyn Gonzalvo |
source |
2 |
| WUSS |
2011 |
Clinical Data Integration for Observational Studies Using Electronic Health Records:Examples with Defining Pregnancy and Gestational Diabetes |
Beinan Zhao |
source |
7 |
| WUSS |
2011 |
JMP Scripting: Advanced Techniques |
Erin Vang |
source |
12 |
| PHUSE EU |
2011 |
An Animated Guide: An Introduction to Latent Class Clustering in SAS |
Russell M. Lavery |
source |
19 |
| PHUSE EU |
2011 |
Defining the Governance and Process of Implementing ADaM across an Organization |
Chris Decker |
source
presentation source |
11 |
| 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 |
SDTM Implementation Guide - Clear as Mud: Strategies for Developing Consistent Company Standards |
Brian Mabe |
source
presentation source |
5 |
| PHUSE EU |
2011 |
Tracing data elements through a standard data flow |
Alistair Dootson |
source
presentation source |
13 |
| MWSUG |
2011 |
Introducing SAS Structural Equation Modeling for JMP: A New User Interface That Brings the Power of SAS/STAT Software to JMP Software |
Wayne E. Watson |
|
18 |
| MWSUG |
2011 |
You Can't Spell 'Assume' without S.A.S. |
Mike D. Tangedal |
|
8 |
| NESUG |
2011 |
An Animated Guide: An Introduction to Latent Class Clustering in SAS |
Russell M. Lavery |
|
16 |
| NESUG |
2011 |
Automating SDTM File Creation: Metadata Files Speeding the Process |
Daphne E. Ewing |
|
7 |
| PharmaSUG |
2011 |
Confessions of a Clinical Programmer: Dragging and Dropping Means Never Having to Say You're Sorry When Creating SDTM Domains |
Janet E. Stuelpner,
Jack Shostak |
source |
12 |
| PharmaSUG |
2011 |
Ensuring Consistent Data Mapping Across SDTM-based Studies - a Data Warehouse Approach |
Annie S. Guo |
source |
12 |
| 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 |
Method to Derive Reproducible SDTM Relationship Datasets |
Suwen Li,
Sai Ma,
Regan Li,
Bob Lan |
source |
9 |
| PharmaSUG |
2011 |
Truncation, Variable Association, Controlled Terminology, and Some Other Pitfalls in the SDTM Mapping Process |
Na Li,
Gary de Jesus,
Daniel Bonzo |
source |
8 |
| SGF |
2011 |
Confessions of a Clinical Programmer: Dragging and Dropping Means Never Having to Say You're Sorry When Creating SDTM Domains |
Janet E. Stuelpner,
Jack Shostak |
source |
12 |
| SGF |
2011 |
Create a Microsoft Excel Pivot Table Using DDE |
Kevin Chung |
source |
10 |
| SGF |
2011 |
Data Mining in SAS with Open-Source Software |
Zhengping Ma |
source |
11 |
| SGF |
2011 |
Healthcare Intelligence: The Challenge of OLAP for Healthcare Data |
John Leveille |
source |
10 |
| SGF |
2011 |
Introducing SAS Structural Equation Modeling: A New User Interface That Brings the Power of SAS/STAT Software to JMP Software |
Wayne E. Watson |
source |
18 |
| SGF |
2011 |
Lets Get Connected: How We Link to our Data |
Jenine Milum |
source |
10 |
| SGF |
2011 |
Macro Design Automation Tool (MDAT): A Methodology for Storing Macro Design Information, Generating Documentation and Code Templates, and Automating Parameter Validation |
Richard L. Schneck,
Mindy Rodgers |
source |
12 |
| SGF |
2011 |
Measures, Members, and Sets, Oh My! Advanced OLAP Techniques |
Stephen M. Overton,
Bryan Stines |
source |
9 |
| SGF |
2011 |
Seamless Dynamic Web Reporting with SAS |
Donald L Penix Jr. |
source |
15 |
| SGF |
2011 |
This SAS Program Says to Google, "What's Up Doc?" |
Scott Davis |
source |
6 |
| SGF |
2011 |
Tick-Tock, Watch the Clock: How Long Will This Take to Run? (or Making SAS Information Maps and SAS Web Report Studio Projects More Efficient) |
Fazal Davood,
Susan M. Jumper |
source |
12 |
| SGF |
2011 |
Using SAS to Help Fight Crime: Scraping and Reporting Inmate Data |
William G. Roehl |
source |
7 |
| NESUG |
2010 |
Automating SDTM File Creation: Metadata Files Speeding the Process |
Daphne E. Ewing |
|
7 |
| NESUG |
2010 |
Counting Drug Exposure in SAS with Interval Graph Modeling |
Xiaoqiang Wang |
|
10 |
| NESUG |
2010 |
Date Conversions in SDTM and ADaM Datasets |
Lily Zhang,
Lili Chen,
Huei-Ling Chen |
|
8 |
| NESUG |
2010 |
Quality Control: How to Analyze and Verify Financial Data |
Michelle M. Duan |
|
5 |
| NESUG |
2010 |
Reading MORE Difficult Raw Data |
Matthew Cohen |
|
9 |
| NESUG |
2010 |
The 5 Biggest Challenges of ADaM |
Terek J. Peterson,
David C. Izard |
|
11 |
| NESUG |
2010 |
The Nitty-Gritty of FDA Electronic Submission: A Programmer's Perspective |
Sandeep N. Beniwal |
|
9 |
| NESUG |
2010 |
TRACKING DATASET DEPENDENCIES IN CLINICAL TRIALS REPORTING |
Binoy Varghese,
Satyanarayana Mogallapu |
|
10 |
| NESUG |
2010 |
Using SAS Output Delivery System (ODS) Markup to Generate Custom Pivot Tables and Pivot Charts |
Chevell T. Parker |
|
24 |
| SCSUG |
2010 |
A SAS Primer for Health Care Data Analysts |
Christopher W. Schacherer |
source |
24 |
| WUSS |
2010 |
Automation of 'makefile' for Use in Clinical Development |
Nalin Tikoo |
source |
7 |
| WUSS |
2010 |
Seamless Dynamic Web Reporting with SAS |
Donald L Penix Jr. |
source |
15 |
| WUSS |
2010 |
Tips for Constructing a Data Warehouse Part 1 |
Curtis A. Smith |
source |
12 |
| WUSS |
2010 |
Tips for Constructing a Data Warehouse Part 2 |
Curtis A. Smith |
source |
11 |
| WUSS |
2010 |
Using SAS Output Delivery System (ODS) Markup to Generate Custom PivotTable and PivotChart Reports |
Chevell T. Parker |
source |
24 |
| PHUSE EU |
2010 |
AstraZENeca and the ART of metadata maintenance |
Paul Frost |
source
presentation source |
11 |
| PHUSE EU |
2010 |
Data Warehousing for the Reporting and Management of Clinical Data |
Robert Ellison |
source
presentation source |
4 |
| PHUSE EU |
2010 |
From ACE to ZINC |
Paul Vervuren |
source |
8 |
| PHUSE EU |
2010 |
The Innovative Medicines Initiative Knowledge Management [presentation] |
Ann Marie Martin |
source |
50 |
| PHUSE EU |
2010 |
The Use of Meta Data in Creating, Transforming and Transporting Clinical Data |
Gregory C. Steffens |
source
presentation source |
9 |
| 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 |
A SAS Primer for Health Care Data Analysts |
Christopher W. Schacherer,
Brent D. Westra |
|
24 |
| MWSUG |
2010 |
Base SAS Methods for Building Dimensional Data Models |
Christopher W. Schacherer |
|
16 |
| MWSUG |
2010 |
Boot Camp for Programmers: Stuff You Need to Know That's Not in the Manual - Best Practices to Help Us Achieve Reproducibility |
Elizabeth Axelrod |
|
7 |
| MWSUG |
2010 |
Introduction to Business Intelligence for SAS Users |
Thomas A. Miron |
|
11 |
| MWSUG |
2010 |
Seamless Dynamic Web Reporting with SAS |
Donald L Penix Jr. |
|
10 |
| MWSUG |
2010 |
The SAS Data Step: Where Your Input Matters |
Peter W. Eberhardt |
|
17 |
| MWSUG |
2010 |
Using SAS Output Delivery System (ODS) Markup to Generate Custom Pivot Tables and Pivot Charts |
Chevell T. Parker |
|
24 |
| SESUG |
2010 |
Customizing Proc Import Code |
Carolyn D. Williams |
source |
3 |
| SESUG |
2010 |
The Data Step; Your Key To Successful Data Processing In SAS |
Donald E. Kros |
source |
13 |
| PharmaSUG |
2010 |
Achieving Efficiency in CDISC-SDTM Conversion and its Challenges - Case Study |
Ilango Ramanujam |
|
6 |
| PharmaSUG |
2010 |
Creating SV and Se First |
Henry B. Winsor,
Mario Widel |
|
7 |
| 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 |
Quality in a World of "Standards" with Differences! |
Sandra VanPelt Nguyen |
|
9 |
| PharmaSUG |
2010 |
Smart Programming and SAE Reconciliation |
Haibin Shu,
Ronen Mansuri,
Maggie Ci Jiang |
|
3 |
| PharmaSUG |
2010 |
The 5 Biggest Challenges of ADaM |
Terek J. Peterson |
|
11 |
| SGF |
2010 |
Automating SDTM File Creation: Speeding Up the Process with Metadata Files |
Daphne E. Ewing |
source |
7 |
| SGF |
2010 |
BI Development for Education by Our Institutional Research Department OR How BI Tools Made Our Motto IR Is Data a Fact |
Ali Y. Yorkos,
Maureen Murray |
source |
10 |
| SGF |
2010 |
Boot Camp for Programmers: Stuff You Need to Know That's Not in the Manual and Best Practices to Help Us Achieve Reproducibility |
Elizabeth Axelrod |
source |
6 |
| SGF |
2010 |
dATa qWaliti 4 Analytics |
David Barkaway,
Gerhard Svolba |
source |
12 |
| SGF |
2010 |
Tabular Reporting Data Standard |
Frederick A. Cieri |
source |
9 |
| SGF |
2010 |
Using SAS Output Delivery System (ODS) Markup to Generate Custom PivotTable and PivotChart Reports |
Chevell T. Parker |
source |
22 |
| SGF |
2010 |
Working with SAS Date and Time Functions |
Andrew H. Karp |
source |
20 |
| SCSUG |
2009 |
SAS Programming Basics |
Clarence W. Jackson |
|
10 |
| SESUG |
2009 |
Boot Camp for Programmers: Stuff You Need to Know That's Not in the Manual - Best Practices to Help Us Achieve Reproducibility |
Elizabeth Axelrod |
source |
7 |
| PHUSE EU |
2009 |
24 Hour Challenge |
Michael Whitworth |
source
presentation source |
6 |
| PHUSE EU |
2009 |
Automation using SAS & C#.NET for CROs and Pharmaceuticals |
Giri Balasubramanina,
Gopinath Viswanathan |
source
presentation source |
13 |
| PHUSE EU |
2009 |
Clinical DI Studio - will we need new MetaProgrammers? |
Simon Wilcock,
Sireesha Potula |
source
presentation source |
11 |
| PHUSE EU |
2009 |
CRT for eCTD submission |
Aurelien Guillouche |
source
presentation source |
8 |
| PHUSE EU |
2009 |
Experiences and lessons learned from a first SDTM submission project |
Paul Vervuren,
Bas van Bakel |
source
presentation source |
12 |
| PHUSE EU |
2009 |
From raw data to submission: A metadata-driven, repository-based process of data conversion to CDISC |
Dimitri Kutsenko |
source
presentation source |
7 |
| PHUSE EU |
2009 |
Insights into ADaM |
Matthew J. Becker |
source
presentation source |
9 |
| PHUSE EU |
2009 |
SDTM Validation: How can we do it right? |
Peter Van Reusel |
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 |
| PHUSE EU |
2009 |
Using SAS Macros to simplify preparation and validation of SDTM data, Annotated CRFs and Define.xml in a metadata driven environment |
Niels Both |
source
presentation source |
10 |
| PHUSE EU |
2009 |
XML Managment Using SAS |
Marco Bertolino |
source |
12 |
| MWSUG |
2009 |
The SAS Data Step: Where Your Input Matters |
Peter W. Eberhardt |
|
17 |
| PNWSUG |
2009 |
Fifty Ways to Lose Your Data (And How to Avoid Them) |
Linda T. Jolley,
Jane Stroupe |
|
20 |
| PNWSUG |
2009 |
Parameter-Driven Data Validation and Transformation Or The Marriage of Microsoft Excel and SAS Macro Variables to Solve ETL Problems |
Hugh Shinn,
Wanda Hopkins |
|
17 |
| NESUG |
2009 |
Boot Camp for Programmers: Stuff You Need to Know That's Not in the Manual - Best Practices to Help Us Achieve Reproducibility |
Elizabeth Axelrod |
|
7 |
| NESUG |
2009 |
LOCF: It's more than just carrying forward |
Vikash Jain,
Niraj J. Pandya |
|
10 |
| NESUG |
2009 |
Simultaneous Migration of SAS Software Versions and Hardware Platforms |
Duggan Collier |
|
13 |
| NESUG |
2009 |
Supporting CDISC Standards in Base SAS Using the SAS Clinical Standards Toolkit |
Peter Villiers |
|
13 |
| WUSS |
2009 |
Simple but Effective SAS-based Automation Techniques to Combine SAS Data Libraries |
Joe Perry |
source |
9 |
| PharmaSUG |
2009 |
CHECK YOUR DATA MORE EFFICIENTLY |
Jian Hua (Daniel) Huang |
|
12 |
| PharmaSUG |
2009 |
Converting CDISC Controlled Terminology to SAS Formats |
Sandeep Juneja,
Vivek Mohan |
|
5 |
| PharmaSUG |
2009 |
Medical Coding System for Clinical Trials - 21 CFR Part 11 Compliant SAS/AF Application |
Annie S. Guo |
|
12 |
| PharmaSUG |
2009 |
Oracle Clinical for SAS Programmers |
Kevin Lee |
|
8 |
| PharmaSUG |
2009 |
Supporting CDISC Standards in Base SAS Using the SAS Clinical Standards Toolkit |
Supporting CDISC Standards |
|
13 |
| PharmaSUG |
2009 |
Your Place or Mine: Data-Driven Summary Statistic Precision |
Nancy Brucken |
|
4 |
| SGF |
2009 |
Boot Camp for Programmers: Stuff You Need to Know That's Not in the Manual |
Elizabeth Axelrod |
source |
7 |
| SGF |
2009 |
Carbon Footprint Modeling with SAS for Sustainability Management: Beyond Calculation |
Keith Renison |
source |
7 |
| SGF |
2009 |
Distribution Interruption Performance Reporting: A Complete Solution |
Chris van der Westhuizen |
source |
10 |
| SGF |
2009 |
Easier Exploratory Analysis for Epidemiology: A Grad Student "How-To" Paper |
Elisa L. Priest,
Brian Adams,
Lori A. Fischbach |
source |
11 |
| SGF |
2009 |
Fifty Ways to Lose Your Data (And How to Avoid Them) |
Linda T. Jolley,
Jane Stroupe |
source |
21 |
| SGF |
2009 |
How to Leverage Oracle Bulk-load for Performance |
Jun Cai |
source |
10 |
| SGF |
2009 |
Supporting CDISC Standards in Base SAS Using the SAS Clinical Standards Toolkit |
Peter Villiers |
source |
13 |
| SGF |
2009 |
Using SAS Data Integration Studio as a Computer-Aided Software Engineering (CASE) Tool |
David M. Kiasi |
source |
16 |
| SGF |
2009 |
You Might Be a SAS Energy Hog If ... |
Michael A. Raithel,
Michael D. Rhoads |
source |
15 |
| SESUG |
2008 |
A SAS Macro for Statistical Power Calculations in Meta-Analysis |
Guy Cafri |
source |
8 |
| SESUG |
2008 |
Parameter-Driven Data Validation and Transformation Or The Marriage of Microsoft Excel and SAS Macro Variables to Solve ETL Problems |
Hugh Shinn,
Wanda Hopkins |
source |
17 |
| SESUG |
2008 |
Two SAS macros for DIF Analysis |
Shiqi Hao |
source |
10 |
| PHUSE EU |
2008 |
CDISC: Implementation Strategies for SDTM |
Brian Mabe |
source |
5 |
| PHUSE EU |
2008 |
ETL and Data Quality: Which Comes First? |
Gregory S. Barnes Nelson,
Emilio J. Power |
source |
10 |
| PHUSE EU |
2008 |
In at the Deep-End (thoughts on mapping multiple studies into CDISC for an ISS/ISE) |
Andrew Noller |
source |
7 |
| PNWSUG |
2008 |
Fast and Efficient Updates to Project Deliverables: The Unix/GNU Make Facility as a Cross-Platform Batch Controller for SAS |
Stephen Hunt |
|
12 |
| NESUG |
2008 |
Analyzing Laboratory Assay Data for Accuracy |
Sara Hickson,
Jeanne Sparrow |
|
13 |
| NESUG |
2008 |
Boot Camp for Programmers: Stuff You Need to Know That's Not in the Manual |
Elizabeth Axelrod |
|
7 |
| NESUG |
2008 |
Clinical-Data Acceptance Testing Procedure |
Sunil Kumar Gupta |
|
15 |
| NESUG |
2008 |
Reading Difficult Raw Data |
Matthew Cohen |
|
7 |
| NESUG |
2008 |
The SAS Data Step: Where Your Input Matters |
Peter W. Eberhardt |
|
18 |
| PharmaSUG |
2008 |
Benefits of Using Bridging Metadata |
Doug Janssen |
|
4 |
| PharmaSUG |
2008 |
Clinical-Data Acceptance Testing Procedure |
Sunil Kumar Gupta |
|
15 |
| PharmaSUG |
2008 |
ETL and Data Quality: Which Comes First? |
Emilio J. Power,
Gregory S. Barnes Nelson |
|
10 |
| PharmaSUG |
2008 |
Fast and Efficient Updates to Project Deliverables: The Unix/GNU Make Facility as a Cross-Platform Batch Controller for SAS |
Make Facility |
|
12 |
| PharmaSUG |
2008 |
SDTM, Plus or Minus |
Barry R. Cohen |
|
6 |
| SGF |
2008 |
CDISC: Pains and Pitfalls of Data Set Creation |
Steven L. Michaelson,
Janet E. Stuelpner |
source |
5 |
| SGF |
2008 |
Clinical-Data Acceptance Testing Procedure |
Sunil Kumar Gupta |
source |
15 |
| SGF |
2008 |
ETL and Data Quality: Which Comes First? |
Emilio J. Power,
Gregory S. Barnes Nelson |
source |
10 |
| SGF |
2008 |
Fast and Efficient Updates to Project Deliverables: The UNIX and GNU Make Facility as a Cross-Platform Batch Controller for SAS |
Brian P. Fairfield-Carter,
Stephen Hunt |
source |
12 |
| SGF |
2008 |
Oracle Clinical for SAS Programmers |
Kevin Lee |
source |
8 |
| SGF |
2008 |
Practical Methods for Creating CDISC SDTM Data Sets from Existing Data |
Robert W. Graebner |
source |
11 |
| SGF |
2008 |
Tabbing Through ODS II |
Haibin Shu |
source |
3 |
| SGF |
2008 |
The Enterprise Melting Pot (Part II) SAS BI The Plan versus Reality (Or, Dont Try This at Home, Kids) |
Gail S. Davidson,
Guinevere Mills |
source |
6 |
| SGF |
2008 |
Three Weeks of Work in 5 Minutes: A Designed Solution for Automatic Reporting and Distribution |
Danni Bayn Jr.,
Richard Koopmann Jr. |
source |
5 |
| SGF |
2008 |
Using DO Statements, Links, and Arrays |
Jimmy A. DeFoor |
source |
13 |
| SGF |
2008 |
Using SAS and Google Earth to Access and Display Air Pollution Data |
Joshua Drukenbrod,
David Mintz |
source |
12 |
| NESUG |
2007 |
Building a Better Bar Chart with SAS/Graph Software |
Perry Watts |
|
20 |
| NESUG |
2007 |
Data Without (Step) Boundaries |
Felix Galbis-Reig |
|
7 |
| NESUG |
2007 |
Oracle Clinical for the SAS Programmer |
Kevin Lee |
|
9 |
| NESUG |
2007 |
The Most Important Efficiency Techniques |
Robert Virgile |
|
11 |
| NESUG |
2007 |
Using Data Integration Studio as a Computer Aided Software Engineering (CASE) Tool |
David M. Kiasi |
|
16 |
| SESUG |
2007 |
A METHODOLOGICAL APPROACH TO PERFORMING CLUSTER ANALYSIS WITH SAS |
William F. McCarthy |
source |
13 |
| SESUG |
2007 |
Benefits of Using Bridging Metadata |
Doug Janssen |
source |
4 |
| WUSS |
2007 |
Data Mining Using SAS Enterprise Miner |
Randall Matignon |
source |
10 |
| WUSS |
2007 |
Detecting Possible Anomalies in Large Data Tables: Methods and Concepts |
Thomas E. Billings |
source |
7 |
| PHUSE EU |
2007 |
All roads lead to SDTM - which one shall we take? |
Ian Fisher,
Donna Thompson |
source |
9 |
| PHUSE EU |
2007 |
Check for SAS files consistency |
Arnaud Dauchy |
source |
29 |
| PHUSE EU |
2007 |
Electronic submissions - the role of the programmer |
Simon Dundas |
source |
8 |
| PHUSE EU |
2007 |
SAS Indexes: Benefits, Limits and Applications |
Carole Beaugendre |
source |
5 |
| SCSUG |
2007 |
Efficiencies of Using Count Data Rather than Raw Data in Regression |
Steve Fleming |
|
10 |
| SCSUG |
2007 |
The Impact of Data Visualization in a Study of Chronic Disease |
Gabe Cano,
Brad Smith,
Paul Cuddihy |
|
17 |
| SCSUG |
2007 |
Using Links, Arrays, and Do-Loops |
Jimmy A. DeFoor |
|
13 |
| PNWSUG |
2007 |
ODS DATA Step Object |
Richard Koopmann Jr. |
|
8 |
| PNWSUG |
2007 |
Using Links, Arrays, and Do-Loops |
Jimmy A. DeFoor |
|
13 |
| PharmaSUG |
2007 |
A Harmonized, Report-Friendly SDTM and ADaM Data Flow |
Aileen L. Yam |
|
4 |
| PharmaSUG |
2007 |
A Scalable Platform For Clinical Trials - Interoperability And Automation In A Web-Based Environment |
John R. Gerlach,
Maulik Shah |
|
11 |
| PharmaSUG |
2007 |
Automatic Creation of Analysis Datasets for Clinical Trials - A Macro Program |
John H. Adams |
|
17 |
| PharmaSUG |
2007 |
Can Coding MedDRA and WHO Drug Be as Easy as a Google Search? |
Sy J. Truong |
|
9 |
| PharmaSUG |
2007 |
CDISC Implementation Step by Step: A Real World Example |
Sy J. Truong |
|
19 |
| PharmaSUG |
2007 |
CDISC: Pains and Pitfalls to Dataset Creation |
Janet E. Stuelpner,
Steven L. Michaelson |
|
5 |
| PharmaSUG |
2007 |
Customizing SAS Data Integration Studio to Generate CDISC Compliant SDTM 3.1 Domains |
Tatyana Kovtun,
John Markle,
Christopher Treglio |
|
12 |
| PharmaSUG |
2007 |
The Use of CDISC Standards in SAS from Data Capture to Reporting |
Andrew T. Fagan |
|
21 |
| SGF |
2007 |
An Animated Guide: PROC TRANSPOSE |
Russell M. Lavery |
source |
22 |
| SGF |
2007 |
Can Coding MedDRA and WHO Drug Be as Easy as a Google Search? |
Sy J. Li,
Na Truong |
source |
9 |
| SGF |
2007 |
Critical Success Factors for Rate Making with SAS Enterprise Miner |
Hrushikesh Khopkar,
Jay King |
source |
17 |
| SGF |
2007 |
Delivering SAS to Excel Jockeys |
Sy J. Xu,
Jing Truong |
source |
10 |
| SGF |
2007 |
Reusable SAS/GRAPH Stored Processes for Dashboarding |
Michael Sherwood,
Rick D. Thomas |
source |
13 |
| SGF |
2007 |
Super Size It!!! Maximize the Performance of Your ETL Processes |
Nancy A. Rausch,
Nancy J. Wills |
source |
14 |
| SGF |
2007 |
The "Ins" and "Outs" of SAS Data Integration Studio |
Chris Weeks,
Tim Olinger |
source |
20 |
| SGF |
2007 |
The Most Important Efficiency Techniques |
Robert Virgile |
source |
11 |
| MWSUG |
2006 |
How to use Summary Statistics as raw data to do basic statistical analysis |
Dachao Liu |
|
6 |
| MWSUG |
2006 |
Leveraging SAS Portal: An Executive Dashboard with Customizable Data Source |
Elibeth R Carpenter |
|
20 |
| MWSUG |
2006 |
Using Biweights for Handling Outliers |
George W Dombi |
|
9 |
| PHUSE EU |
2006 |
Base SAS vs. SAS Data Integration Studio: Understanding ETL and the SAS Tools Used to Support It |
Danny Grasse,
Gregory S. Barnes Nelson |
source |
20 |
| PHUSE EU |
2006 |
The Use of CDISC Standards in SAS from Data Capture to Reporting |
Andrew T. Fagan |
source |
21 |
| SESUG |
2006 |
Stars and Models: How to Build and Maintain Star Schemas Using SAS Data Integration Server in SAS9 |
Nancy A. Rausch |
source |
24 |
| SESUG |
2006 |
The "Ins" and "Outs" of SAS Data Integration Studio |
Christopher R. Olinger |
source |
17 |
| WUSS |
2006 |
An Approach Finding the Right Tolerance Level for Clinical Data Acceptance |
Karen Walker |
source |
5 |
| WUSS |
2006 |
How to Leverage Oracle Bulk-load for Performance |
Jun Cai |
source |
10 |
| WUSS |
2006 |
Introduction to Formats: Simplifying Programming and Improving Data Presentation |
Elizabeth A. Roth |
source |
11 |
| NESUG |
2006 |
"Best-in-Class" Comparison Group (BCCG) Methodology for Process of Care Performance Indicators |
William F. McCarthy,
Nan Guo |
|
10 |
| NESUG |
2006 |
Using SAS Data Integration Studio to Convert Clinical Trials Data to the CDISC SDTM Standard |
Barry R. Cohen |
|
8 |
| PharmaSUG |
2006 |
A Case of Online Data Processing and Statistical Analysis via SAS/IntrNet |
Sijian Zhang |
|
8 |
| PharmaSUG |
2006 |
Base SAS vs. SAS Data Integration Studio: Understanding ETL and the SAS Tools Used to Support It |
Danny Grasse,
Gregory S. Barnes Nelson |
|
20 |
| PharmaSUG |
2006 |
CDISC Implementation, Real World Applications |
Sy J. Truong |
|
26 |
| PharmaSUG |
2006 |
Using SAS ETL Studio to Convert Clinical Trials Data to the CDISC SDTM |
Barry R. Cohen |
|
10 |
| SUGI |
2006 |
"Best-in-Class" Comparison Group (BCCG) Methodology for Process of Care Performance Indicators |
William F. McCarthy,
Nan Guo |
source |
10 |
| SUGI |
2006 |
Base SAS vs. SAS Data Integration Studio: Understanding ETL and the SAS Tools Used to Support It |
Danny Grasse,
Gregory S. Barnes Nelson |
source |
20 |
| SUGI |
2006 |
Litigation Data Analysis/Auditing/ETL for BI: Triplets Separated at Birth |
Nicholson E. Warman |
source |
15 |
| SUGI |
2006 |
SAS Enterprise Guide Stored Processes, Part 1: The Information Consumer's View |
Marje Fecht,
Peter R. Bennett |
source |
21 |
| SUGI |
2006 |
SAS Enterprise Guide Stored Processes, Part 2: Creation and Deployment |
Marje Fecht,
Peter R. Bennett |
source |
21 |
| SUGI |
2006 |
Save Those Eyes: A Quality-Control Utility for Checking RTF Output Immediately and Accurately |
Michael Hagendoorn,
Jonathan M. Squire,
Johnny Tai |
source |
10 |
| SUGI |
2006 |
Stars and Models - How to Build and Maintain Star Schemas Using SAS ETL Server |
Nancy A. Rausch |
source |
24 |
| SUGI |
2006 |
The Ins and Outs of SAS ETL Studio |
Christopher R. Olinger,
Tim Weeks |
source |
17 |
| SESUG |
2005 |
Automated Excel-lent Validation |
Janet E. Stuelpner |
source |
9 |
| SESUG |
2005 |
Once Again on Efficiency and Base SAS |
Milorad Stojanovic |
source |
6 |
| SESUG |
2005 |
Simplify Existing Projects with Ideas from Data Warehousing |
Rick Aster |
source |
6 |
| SESUG |
2005 |
The SAS Data Step: Where Your Input Matters |
Peter W. Eberhardt |
source |
17 |
| SESUG |
2005 |
Use a SAS Database Search Engine Instead of Writing a Program |
Eugene Yeh |
source |
10 |
| SESUG |
2005 |
Using SAS Enterprise ETL Server to Build a Data Warehouse: Focus on Student Enrollment Data |
Evangeline Collado |
source |
6 |
| PHUSE EU |
2005 |
Complex Laboratory Data, Strategies and Tools for a Way out of the Maze |
Benjamin Szilagyi,
Christof Binder |
source |
4 |
| PHUSE EU |
2005 |
Customer oriented CDISC implementation |
Edelbert Arnold,
Ulrike Plank |
source
poster source |
13 |
| PHUSE EU |
2005 |
Designing a Global SAS9 Architecture for Clinical Trials Analysis and Reporting |
Gregory S. Barnes Nelson,
Michael Walega |
source |
12 |
| PHUSE EU |
2005 |
Integrating SAS With Open Software in a Validated Drug Safety Environment |
Jeremy Fletcher |
source |
48 |
| PHUSE EU |
2005 |
ODM & define.xml |
David Iberson-Hurst |
source |
58 |
| PHUSE EU |
2005 |
Only Interactive Graphics Will Do |
Nelson Kinnersley |
source |
4 |
| PHUSE EU |
2005 |
The Future of CDISC |
Becky Kush |
source |
50 |
| MWSUG |
2005 |
Introduction To SAS Business Intelligence/Enterprise Guide |
Alex Dmitrienko |
|
13 |
| WUSS |
2005 |
Deployment of a Data Transfer Application Using PROC SQL and Nested Macros |
Keh-Dong Shiang |
source |
8 |
| WUSS |
2005 |
Transforming Data for CDISC and ISS |
Sy J. Truong |
source |
11 |
| NESUG |
2005 |
An Animated Guide: PROC TRANSPOSE |
Russell M. Lavery |
|
9 |
| NESUG |
2005 |
Beyond FORMAT Basics |
Michael S. Zdeb |
|
20 |
| PharmaSUG |
2005 |
An Approach Finding the Right Tolerance Level for Clinical Data Acceptance |
Karen Walker |
|
6 |
| PharmaSUG |
2005 |
Automated Excel-lent Validation |
Janet E. Stuelpner |
|
9 |
| PharmaSUG |
2005 |
CDISC for electronic submissions - A Table Translation Program |
John H. Adams,
Boehringer Ingelheim |
|
15 |
| PharmaSUG |
2005 |
Managing a SAS Programming Environment Using Data Access Pages and the Microsoft Office Data Source Control |
Brian P. Fairfield-Carter |
|
12 |
| PharmaSUG |
2005 |
Program Flow Design for Efficient CRT Programming |
Sam Mao |
|
10 |
| 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 |
The Use and Abuse of the Program Data Vector (The Procs) |
Jim Johnson |
|
17 |
| PharmaSUG |
2005 |
Use ODS Generating Patient Profiles |
Haibin Shu,
Bala Cynwyd |
|
6 |
| PharmaSUG |
2005 |
Using Procedure-Based ODS Data Components in Statistical Reporting |
Vincent J. Faber |
|
10 |
| SUGI |
2005 |
An Introduction to SAS Applications of the Windows Scripting Host |
Brian P. Fairfield-Carter,
Stephen Hunt,
Tracy Sherman |
source |
10 |
| SUGI |
2005 |
Are You Ready to Roll? SAS9 Implementation Lessons Learned |
Tim Walters |
source |
7 |
| SUGI |
2005 |
Designing a Global SAS9 Architecture for Clinical Trials Analysis and Reporting |
Gregory S. Barnes Nelson,
Michael Walega |
source |
12 |
| SUGI |
2005 |
End-to-End Web Reporting Using SAS Enterprise Guide 3.0: Who Does What and When |
Marje Fecht,
Peter R. Bennett |
source |
14 |
| SUGI |
2005 |
ETL: The Heavy Lifting That Makes BI Possible |
Ralph Kimball |
source |
11 |
| SUGI |
2005 |
I'll Have the PROC TABULATE a la ODS Please, with a Table of Contents on the Side |
Ray Pass |
source |
10 |
| SUGI |
2005 |
Introducing SAS Forecast Studio |
Michael J. Leonard,
Brenda Wolfe,
Paddy Fahey |
source |
16 |
| SUGI |
2005 |
Managing a SAS Programming Environment Using Data Access Pages and the Microsoft Office Data Source Control |
Brian P. Fairfield-Carter |
source |
10 |
| SUGI |
2005 |
PreMIS: Pre-hospital Medical Information System |
Jeff Wright,
Patrick H. Alston,
Sharon Schiro,
Tim Walters |
source |
12 |
| SUGI |
2005 |
Simplify Existing Projects with Ideas from Data Warehousing |
Rick Aster |
source |
6 |
| SUGI |
2005 |
Slicing and Dicing the SAS Data Set |
William C. Murphy |
source |
5 |
| SUGI |
2005 |
The SAS Data Step: Where Your Input Matters |
Peter W. Eberhardt |
source |
17 |
| SUGI |
2005 |
Using Procedure-Based ODS Data Components in Statistical Reporting |
Vincent J. Faber |
source |
10 |
| NESUG |
2004 |
How to develop SAS data mart in one day (with code examples!) |
Tanya Kolosova,
Samuel Berestizhevsky |
|
10 |
| SCSUG |
2004 |
Just for the Kids School Reports: A data-oriented web site powered by SAS |
Bob Zambarano |
|
14 |
| SESUG |
2004 |
1 Matching SAS Data Sets: If at First You Don't Succeed, Match, Match Again |
Imelda C. Go |
source |
10 |
| SESUG |
2004 |
The SAS Data Step: Where Your Input Matters |
Peter W. Eberhardt |
source |
17 |
| WUSS |
2004 |
Design Principles for Online Information: Readability, Usability, and Accessibility |
Jodie M. Gilmore |
source |
16 |
| WUSS |
2004 |
Reading and Writing XML Files from SAS |
Miriam Cisternas,
Ricardo A. Cisternas |
source |
18 |
| WUSS |
2004 |
Successful FDA Advisory Meetings by using Analysis Datasets |
Sandy Chang,
Steven Wong |
source |
10 |
| WUSS |
2004 |
Working with SAS Date and Time Functions |
Andrew H. Karp |
source |
12 |
| MWSUG |
2004 |
Data Quality and the Big 'D' |
Elizabeth Axelrod |
|
4 |
| MWSUG |
2004 |
Using SAS/Access to save time and automate non SAS processing steps |
Timothy J. Stires |
|
4 |
| PNWSUG |
2004 |
Reading and Writing XML Files from SAS |
Peter J. Lund |
|
|
| PharmaSUG |
2004 |
A SAS Database Search Engine Gives Everyone the Power to Know |
Eugene Yeh |
|
11 |
| PharmaSUG |
2004 |
An Introduction to SAS Applications of the Windows Scripting Host |
Stephen Hunt |
|
12 |
| PharmaSUG |
2004 |
CDX - clinical data management and report programming environment |
Gunilla Sköllermo,
Pål Edman |
|
7 |
| PharmaSUG |
2004 |
Defining and Validating CDISC Data Standards to XML in SAS Technology |
Anthony L. Friebel |
|
6 |
| PharmaSUG |
2004 |
How SAS Thinks or Why the DATA Step Does What It Does |
Neil H. Howard |
|
17 |
| PharmaSUG |
2004 |
Programming Tips and Examples for Your Toolkit |
John Morrill,
Kristi Wiser |
|
8 |
| PharmaSUG |
2004 |
Reading and Writing XML Files from SAS |
Miriam G. Cisternas |
|
18 |
| PharmaSUG |
2004 |
Tools to Facilitate the Creation of Pooled Clinical Trials Databases |
Patricia Majcher |
|
8 |
| SUGI |
2004 |
A Day in the Life of an Analytical Warehouse |
Julian Anderson,
Gregory S. Barnes Nelson,
Jeff Wright |
source |
16 |
| SUGI |
2004 |
A SAS Database Search Engine Gives Everyone the Power to Know |
Eugene Yeh |
source |
11 |
| SUGI |
2004 |
How SAS Thinks or Why the DATA Step Does What It Does |
Neil H. Howard |
source |
19 |
| SUGI |
2004 |
Model-Based Multiple Imputation |
Geoffrey Paulin,
Shirley Tsai,
Melissa Grance |
source |
13 |
| SUGI |
2004 |
Reading and Writing XML Files from SAS |
Miriam G. Cisternas,
Ricardo A. Cisternas |
source |
19 |
| SUGI |
2004 |
Real Time Decision Support: Creating a Flexible Architecture for Real Time Analytics |
Gregory S. Barnes Nelson |
source |
13 |
| SUGI |
2004 |
Some Uses (and Handy Abuses) of PROC TRANSPOSE |
Ralph W. Leighton |
source |
17 |
| SUGI |
2004 |
Using Text Files to Enhance SAS Code |
David J. Austin |
source |
11 |
| SUGI |
2004 |
Write SAS Code to Generate Another SAS Program - A Dynamic Way to Get Your Data into SAS |
Linda Gau |
source |
9 |
| WUSS |
2003 |
Batch Automated Reporting and Analysis in Semiconductor Manufacturing Parametrics |
Tom Winter,
Willy Waks |
source |
10 |
| WUSS |
2003 |
Ka-Ching! A New Cash Register Report From SAS In 6 Easy Steps! |
Nikki M. Carroll |
source |
4 |
| WUSS |
2003 |
MedDRA Made Easy with SAS/IntrNet |
Sy J. Truong |
source |
9 |
| WUSS |
2003 |
Whittle While You Work-Looking Less Dopey Using SAS Efficiencies (And Make Your Clients Go From Grumpy To Happy) |
Nikki Carroll,
Frank A. Ferriola |
source |
5 |
| WUSS |
2003 |
Write SAS Code To Generate Another SAS Program -- A Dynamic Way To Get Your Data Into The SAS System |
Linda Gau |
source |
5 |
| SESUG |
2003 |
A Technique for Storing and Manipulating Incomplete Dates in a Single SAS Date Value |
John Ingersoll |
source |
8 |
| SESUG |
2003 |
An Animated Guide: Proc Report: The File Behind the Scenes |
Russell M. Lavery |
source |
10 |
| SESUG |
2003 |
Musical Macros: A Soothing Solution for a Recurrent Data Step Headache |
Philip J. d'Almada |
source |
3 |
| SESUG |
2003 |
Working with SAS Date and Time Functions |
Andrew H. Karp |
source |
9 |
| MWSUG |
2003 |
Missing observations: Identification and resolutions using the SAS System |
Doug Moore,
Tahereh Nourbakhsh |
|
14 |
| MWSUG |
2003 |
Working with SAS Data and Time Functions |
Andrew H. Karp |
|
9 |
| NESUG |
2003 |
Poor Man's OLAP: A MDDB Reporting Application Using Base SAS |
John D. Chapman |
|
10 |
| NESUG |
2003 |
Presenting Lab Data Using AF and Spreadsheet Template |
Haibin Shu |
|
5 |
| NESUG |
2003 |
Reading External Files Using SAS Software |
Clinton S. Rickards |
|
9 |
| SEUGI |
2003 |
AstraZeneca Data Migration Project [presentation] |
David Smith,
Paul Frost |
source |
39 |
| SEUGI |
2003 |
Best Practices in Data Warehousing Design and Implementation [presentation] |
Rein Mertens |
source |
32 |
| SEUGI |
2003 |
Strategic Business Decisions powered by OLAP [presentation] |
Ingo Brenckmann |
source |
18 |
| PharmaSUG |
2003 |
Capabilities and Example Uses of a SAS Macro for Summary Reporting of Clinical Data |
James T. Decker,
Jun Wang |
|
8 |
| PharmaSUG |
2003 |
Developing "EXSAS" an integrated system for statistical analysis of non-clinical experimental data using animals |
Chikuma Hamada |
|
6 |
| PharmaSUG |
2003 |
Standardizing Data Processing and e-Publishing for the Pharmaceutical Industry |
Shawn Wang |
|
6 |
| SUGI |
2003 |
A Table-Driven Solution for Clinical Data Submission |
Jim Sattler |
source |
6 |
| SUGI |
2003 |
Better Decisions Through Better Data |
Tony Fisher,
George Marinos |
source |
6 |
| SUGI |
2003 |
Date Handling in the SAS System |
Bruce F. Gilsen |
source |
10 |
| SUGI |
2003 |
Describing and Retrieving Data with SAS Formats |
David H. Johnson |
source |
11 |
| MWSUG |
2002 |
Customization to the SAS Multidimensional Report Viewer |
Karl Schaefer,
Steve Wagar,
Sarah L. Mitchell,
Alan Leach |
|
8 |
| SCSUG |
2002 |
Heart Valve Size Estimates Using Body Indices |
O. M. Little |
|
7 |
| NESUG |
2002 |
Date Handling in the SAS System |
Bruce F. Gilsen |
|
10 |
| SESUG |
2002 |
DATA Step Essentials |
Neil H. Howard |
source |
10 |
| WUSS |
2002 |
A Macro to Perform a T-Test for Two Independent Samples Using Sufficient Statistics |
Lang-Feng Tsai |
source |
5 |
| WUSS |
2002 |
Structural Equation Modeling: Easy Solutions Using SAS |
Shuqiang Zhang |
source |
5 |
| SEUGI |
2002 |
Creating a customer event based data warehouse [presentation] |
David Porter |
source |
35 |
| SEUGI |
2002 |
Innovations in Cash Logistics: CoBaCash - An intranet based system for optimizing cash supply for branches and ATMs [presentation] |
A. Ruban,
L. Nottekämper |
source |
25 |
| PharmaSUG |
2002 |
Data Exploration in the Pharmaceutical Industry |
Andrew T. Fagan |
|
8 |
| PharmaSUG |
2002 |
Preparing the SAS Software Programming Environment for Regulatory Submission |
Sunil Kumar Gupta |
|
10 |
| SUGI |
2002 |
A Scorecard Approach to Improving Data Quality |
Phil Nousak,
Robert W. Phelps |
source |
9 |
| SUGI |
2002 |
Data Warehousing in the Modern World: A Case Study Revisited |
Mary K. Tucker |
source |
8 |
| SUGI |
2002 |
Some Uses (and Handy Abuses) of PROC TRANSPOSE |
Ralph W. Leighton |
source |
10 |
| MWSUG |
2001 |
Data Warehousing: A Technology Update and Review |
Vernon Hoffner |
|
9 |
| MWSUG |
2001 |
Development of Automated Test Scoring Using the SAS System |
Jon M Patton |
|
4 |
| MWSUG |
2001 |
Working with SAS Date and Time Functions |
Andrew H. Karp |
|
7 |
| NESUG |
2001 |
I'll Have the TABULATEs a la ODS Please, With a Table of Contents On the Side |
Ray Pass |
|
9 |
| NESUG |
2001 |
Some Uses (and Handy Abuses) of PROC TRANSPOSE |
Ralph W. Leighton |
|
10 |
| NESUG |
2001 |
Use SAS to Maintain and QC your Database |
Sergey Sian |
|
4 |
| SESUG |
2001 |
A Scorecard Approach to Improving Data Quality |
Robert W. Phelps,
Phil Nousak |
source |
9 |
| SCSUG |
2001 |
A Scorecard Approach to Improving Data Quality |
Robert W. Phelps,
Phil Nousak |
|
9 |
| SCSUG |
2001 |
Energizing End Users with a Slice of SAS and a Cup of Jave |
Randy Curnutt,
Michael J. Pell,
John M. LaBore |
|
5 |
| SEUGI |
2001 |
Customer Profiling System in Telecom Italia Mobile [presentation] |
Claudio Bocci,
Gianni Santerini |
source |
44 |
| SEUGI |
2001 |
Intranet-based Information Delivery at Central-European International Bank [presentation] |
Eva Habori |
source |
25 |
| SEUGI |
2001 |
Overcoming Cross-Platform Issures using SAS/Connect and Java |
John M. LaBore,
Michael J. Pell,
Randy Curnutt |
source |
5 |
| SEUGI |
2001 |
Software Validation in Clinical Trial Reporting: Experiences from the Biostatistical & Data Sciences Department [presentation] |
Andrea Baker |
source |
25 |
| 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 spider in the Web for your everyday HR business - Corporate human resources data warehouse for logistical service provider [presentation] |
Niels Stout |
source |
25 |
| SEUGI |
2001 |
WELFARE - Wells, Field Analysis, Reservoir Evaluation [presentation] |
C. Mouret,
J. F. Coste,
J. P. Valois |
source |
50 |
| PharmaSUG |
2001 |
An Analysis Programming Process Focused on Data Derivation |
Lee Walke |
|
4 |
| PharmaSUG |
2001 |
Developing a SAS Macro Library to Create Standard Clinical Data Summary Reports |
Chad W. Melson,
James T. Decker |
|
10 |
| PharmaSUG |
2001 |
Energizing End Users with a Slice of SAS and a Cup of Java |
Randy Curnutt,
Michael J. Pell,
John M. LaBore |
|
6 |
| SUGI |
2001 |
A Case Study in Data Warehousing and Data Mining Using the SAS System |
Mary K. Tucker |
source |
3 |
| SUGI |
2001 |
Comparing Pairs: The Array's the Thing |
Mary F. MacDougall |
source |
3 |
| SUGI |
2001 |
Data Modeling in Clinical Data Analysis Projects |
Gajanan Bhat |
source |
6 |
| SUGI |
2001 |
Dynamic Applications to Satisfy an Ever Changing World |
Bernard R. Poisson |
source |
4 |
| SUGI |
2001 |
I'll Have the TABULATEs a la ODS Please, With a Table of Contents On the Side |
Ray Pass |
source |
9 |
| SUGI |
2001 |
Preparing the SAS Software Programming Environment for Regulatory Submission |
Sunil Kumar Gupta |
source |
9 |
| SUGI |
2001 |
The Phoenix: Creating Applications which Outlive Current Users |
Jeff LeSueur,
Dana Rafiee |
source |
4 |
| SUGI |
2001 |
Tips for Using PROC SQL to Extract Information from Medical Claims Data Sets |
Clayton Wells |
source |
4 |
| SUGI |
2001 |
Using SAS Enterprise Miner for Forecasting |
Kattamuri S. Sarma |
source |
6 |
| SESUG |
2000 |
I'll Have the TABULATEs a la ODS Please, With a Table of Contents On the Side |
Ray Pass |
source |
9 |
| NESUG |
2000 |
A Coding History for Clinical Data |
Phyllis Wolf |
|
2 |
| NESUG |
2000 |
Avoiding Mayhem in the New Millennium: Working with Missing Data |
JoAnn R. Matthews |
|
10 |
| NESUG |
2000 |
Batch Processing with SAS: Beyond Running Programs Overnight |
Lisa Sanbonmatsu |
|
2 |
| NESUG |
2000 |
I'll Have the TABULATEs a la ODS Please, With a Table of Contents On the Side |
Ray Pass |
|
9 |
| NESUG |
2000 |
SAS Online Data Archive for Population Studies |
David Barro,
Leslie Benson,
Steve Maczuga,
Cindy Mitchell,
Jeanne M. Spicer |
|
6 |
| NESUG |
2000 |
Some Uses (and Handy Abuses) of PROC TRANSPOSE |
Ralph W. Leighton |
|
12 |
| NESUG |
2000 |
Working with SAS Date and Time Functions |
Andrew H. Karp |
|
7 |
| WUSS |
2000 |
ODS for Dummies |
Christopher R. Ollinger |
source |
9 |
| MWSUG |
2000 |
Advanced DATA Step Techniques |
Neil H. Howard |
|
10 |
| MWSUG |
2000 |
Merges and Joins |
Timothy J. Harrington |
|
6 |
| SEUGI |
2000 |
a data warehouse solution in Swiss managed health care [presentation] |
Georg A. Mathias,
Ulrich Thurnheer |
source |
33 |
| SEUGI |
2000 |
Clinical Data Warehousing Functionality [presentation] |
Michael Roberson |
source |
39 |
| SEUGI |
2000 |
CRM Out of the Box - An Integrated Turnkey Solution [presentation] |
Frank Block |
source |
25 |
| SEUGI |
2000 |
Data Warehouse and Analytical Tools - Development and Implementation [presentation] |
David Frazer |
source |
43 |
| SEUGI |
2000 |
Data Warehouse on administrative data of enterprises [presentation] |
Giovanna Del Mondo |
source |
23 |
| SEUGI |
2000 |
E.S.S.E. Editing Systems Standard Evaluation - Software Framework [presentation] |
A. Manzari,
G. Della Rocca,
M. Di Zao,
O. Luzi |
source |
20 |
| SEUGI |
2000 |
Feeding the Warehouse: How we satisfied the Hunger of the Beast called Miami [presentation] |
Gareth Hughes,
Mel Cullen |
source |
39 |
| SEUGI |
2000 |
IBIS-Integrated Business Information System [presentation] |
Kirsteen MacLeqan |
source |
35 |
| SEUGI |
2000 |
If you lose FOCUS, You can always count on SAS [presentation] |
Manjou Parmar |
source |
21 |
| SEUGI |
2000 |
Implementation of an International SAS Programming Environment for Clinical Trials [presentation] |
Adrienne M. Jenn |
source |
24 |
| SEUGI |
2000 |
Ministry of Trade and Industry Yritti Web Reporting System for Enterprise Supports Follow up [presentation] |
Armi Sundstrom,
Marko Kivela,
Raimo Porttikivi |
source |
20 |
| SEUGI |
2000 |
ODS for Dummies [presentation] |
Christopher R. Olinger |
source |
36 |
| SEUGI |
2000 |
Practical Tips and Techniques for Building an Enterprise Data Warehouse in an IBM environment |
John Finianos,
Jugdish Mistry |
source |
6 |
| SEUGI |
2000 |
SAS environment harnessed to reporting system execution at the customs distributed structure [presentation] |
Tadeusz Lewandowski,
Wojciech Bułakowski |
source |
50 |
| SEUGI |
2000 |
Was The Y2K Moratorium A Blessing In Disguise For Data Warehousing? [presentation] |
Paul W. Johnson |
source |
14 |
| PharmaSUG |
2000 |
Clinical Data Warehouse Functionality |
Peter Villiers |
|
5 |
| PharmaSUG |
2000 |
Creating Multiple SAS Data Sets from an ASCII File |
Archie Medrano |
|
6 |
| PharmaSUG |
2000 |
Data Modeling in Clinical Data Analysis Projects |
Gajanan Bhat |
|
3 |
| SUGI |
2000 |
Advanced DATA Step Techniques |
Neil H. Howard |
source |
10 |
| SUGI |
2000 |
Avoiding Mayhem in the New Millennium: Working with Missing Data |
JoAnn R. Matthews |
source |
10 |
| SUGI |
2000 |
Convert Your Model T into a Ferrari - Unleash the MDDB |
Ian J. Sutton |
source |
7 |
| SUGI |
2000 |
Dynamic Dataset Selection and Project Management using SAS 6.12 and the Windows NT 4.0 File System |
Matthew T. Downs,
Heidi M. Christ-Schmidt |
source |
5 |
| SUGI |
2000 |
Merges and Joins |
Timothy J. Harrington |
source |
6 |
| SUGI |
2000 |
Minimizing Development Risk While Maximizing Warehouse Performance on UNIX Systems |
Jeff LeSueur |
source |
5 |
| SUGI |
2000 |
ODS for Dummies |
Christopher R. Olinger |
source |
10 |
| SCSUG |
1999 |
Y2K Windowed Two Digit Years and When to Use YEARCUTOFF |
Clarence W. Jackson |
|
4 |
| SCSUG |
1999 |
Year 2000 Triage For Your SAS Applications |
Mike Kalt |
|
7 |
| SESUG |
1999 |
Year 2000 Triage For Your SAS Applications |
Mike Kalt |
source |
7 |
| WUSS |
1999 |
Constructing a Data Warehouse as the Foundation for a Client/Serveer Application System |
Curtis A. Smith |
source |
8 |
| WUSS |
1999 |
Working with SAS Date and Time Functions |
Andrew H. Karp |
source |
8 |
| WUSS |
1999 |
Year 2000 Triage For Your SAS Applications |
Mike Kalt |
source |
7 |
| NESUG |
1999 |
Robust Programming Techniques in the SAS System |
Alice M. Cheng |
|
10 |
| NESUG |
1999 |
Some Uses (and Handy Abuses) of PROC TRANSPOSE |
Ralph W. Leighton |
|
10 |
| NESUG |
1999 |
Visual Analysis on the WEB: Animating High Density Multidimensional Data |
Haftan M. Eckholdt |
|
9 |
| NESUG |
1999 |
Year 2000 Triage For Your SAS Applications |
Mike Kalt |
|
7 |
| MWSUG |
1999 |
Working with SAS Date and Time Functions with Reference to Year 2000 Issues |
Andrew H. Karp |
|
7 |
| MWSUG |
1999 |
Year 2000 Triage For Your SAS Applications |
Mike Kalt |
|
7 |
| SEUGI |
1999 |
A Data Warehouse on Auto-Pilot - how to maintain your SAS Data Warehouse without programming [presentation] |
Steve Morton |
source |
40 |
| SEUGI |
1999 |
Data warehouse on the Web |
Attila Papp,
Eva Torda,
Rózsa Tóth |
source |
4 |
| SEUGI |
1999 |
Financial Management at a Commercial Bank [presentation] |
Tadeusz Stawicki |
source |
19 |
| SUGI |
1999 |
Adding Extensions to the SAS/Warehouse Administrator |
Peter R. Welbrock |
source |
10 |
| SUGI |
1999 |
Automated Input Interface for SAS Batch-Mode Processing |
S. Patrick Thornton |
source |
4 |
| SUGI |
1999 |
CFO Vision at Centra Health, A Successful Partnership |
Julie A. Maddox,
John Wimmer,
Billy Dunn |
source |
9 |
| SUGI |
1999 |
Constructing a Data Warehouse |
Curtis A. Smith |
source |
6 |
| SUGI |
1999 |
Implementing SAS IT Charge Manager at the State of Wisconsin |
Bruce R. McClinton |
source |
6 |
| SUGI |
1999 |
Practical Tips and Techniques for Building an Enterprise Data Warehouse in an IBM Mainframe Environment |
Jugdish Mistry,
John Finianos |
source |
6 |
| SUGI |
1999 |
Reading External Files Using SAS Software |
Clinton S. Rickards |
source |
9 |
| SUGI |
1999 |
Robust Outlier Identification using SAS |
Jack N. Shoemaker |
source |
8 |
| SUGI |
1999 |
Untangling and Reformatting NT PerfMon Data to Load a UNIX SAS Database with a Software-Intelligent Data-Adaptive Application |
Heather M. McDowell,
LeRoy Bessler |
source |
6 |
| SUGI |
1999 |
Working with SAS Date and Time Functions |
Andrew H. Karp |
source |
7 |
| SUGI |
1999 |
Year 2000 Issues for SAS Users |
Mike Kalt,
Richard D. Langston |
source |
7 |
| MWSUG |
1998 |
If There Is A Will, There Is A Way: Getting Around Defaults of PROC LOGISTIC |
Chao-Ying Joanne Peng,
Tak-Shing Harry So |
|
10 |
| SCSUG |
1998 |
Data Warehouse: How to Use SAS from Beginning to Almost Ending for Year |
Akbar Golmirzaie |
|
6 |
| WUSS |
1998 |
Constructing a Data Warehouse |
Curtis A. Smith |
source |
5 |
| WUSS |
1998 |
Quick Results from Statistical Analysis - An Alternative Approach to the Popular Menu Interface Systems |
George C. J. Fernandez |
source |
8 |
| WUSS |
1998 |
Working with SAS Date and Time Functions |
Andrew H. Karp |
source |
7 |
| NESUG |
1998 |
Advanced Techniques to Build and Manage User-Defined SAS Format Catalogs |
Jack N. Shoemaker |
|
6 |
| NESUG |
1998 |
SAS Makes Reproducing Easy |
Carolyn Kuntz |
|
6 |
| NESUG |
1998 |
Working with SAS Date and Time Functions With Reference to Year 2000 |
Andrew H. Karp |
|
8 |
| SESUG |
1998 |
A Simplified Reporting Strategy: "Summary" Data Sets for Reporting on Data from Multiple Source Data Sets |
Steve Ross |
|
6 |
| SESUG |
1998 |
Data Warehouse: How to Use SAS from Beginning to Almost Ending for Your Warehouse |
Akbar Golmirzaie |
|
7 |
| SESUG |
1998 |
It's Almost the Year 2000 - Should I Panic? |
Mike Kalt |
|
8 |
| PNWSUG |
1998 |
Working with SAS Date and Time Funcitons |
Andrew H. Karp |
|
8 |
| SEUGI |
1998 |
An introduction to the PH-Template Developer's Kit extension to SAS/PH-Clinical [presentation] |
Alan Reading |
source |
15 |
| SEUGI |
1998 |
Data Warehousing and application development using client/server computing |
Miroslav Orlovsky,
Veronika Hornikova |
source |
12 |
| SEUGI |
1998 |
Module for the Central Bank Analysis of Economic Situation of Enterprises |
Piotr Boguszewski |
source |
13 |
| SEUGI |
1998 |
Using CIDS, a SAS/AF software application, to build a data warehouse and to provide OLAP tools for managers at PTT Post |
Harm Schipper |
source |
10 |
| PharmaSUG |
1998 |
Development of Global Reporting Systems for the Hoechst Marion Roussel Inc. |
Dorothy Hu Huang,
I. Outline |
|
7 |
| SUGI |
1998 |
Data Extraction Methods in Medium and Large Databases |
Anthony M. Dymond |
source |
6 |
| SUGI |
1998 |
Data Warehouse: How to Use SAS from Beginning to Almost Ending for Your Warehouse |
Akbar Golmirzaie |
source |
7 |
| SUGI |
1998 |
Data Warehousing and the Web |
Jim Davis |
source |
4 |
| SUGI |
1998 |
Working with SAS Date and Time Functions |
Andrew H. Karp |
source |
7 |
| WUSS |
1997 |
A Fast and Robust Method for Pattern Matching in Time Series Databases |
Eamonn Keogh |
source |
6 |
| WUSS |
1997 |
Constructing a Data Warehouse |
Curtis A. Smith |
source |
6 |
| WUSS |
1997 |
The SAS Multidimensional Database and Its Uses in Application Development |
Bill Powers |
source |
5 |
| 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 |
Working with SAS Date and Time Functions |
Andrew H. Karp |
source |
7 |
| NESUG |
1997 |
A Non-Memory Intensive Alternative to PROC MEANS and PROC SUMMARY |
Jack Yang |
|
4 |
| NESUG |
1997 |
Paper-less Reporting: Online Data Review and Analysis Using SAS/PH-Clinical Software |
Eileen Ching |
|
5 |
| NESUG |
1997 |
SAS Macro Solutions: An Application to Get You Going |
Ralph W. Leighton |
|
10 |
| NESUG |
1997 |
SELECT ITEMS FROM PROC.SQL WHERE ITEMS > BASICS |
Alan Dickson,
Ray Pass |
|
10 |
| MWSUG |
1997 |
A SAS Macro System to Automate the Decoding and Validation of Data |
Carl R. Haske,
Kayhan Najmabadi |
|
5 |
| MWSUG |
1997 |
Working with SAS Date and Time Functions |
Andrew H. Karp |
|
7 |
| SESUG |
1997 |
Exploring Data With Base SAS Software |
Thomas J. Winn Jr. |
|
7 |
| SEUGI |
1997 |
Analytical information system for accident monitoring at the Russian transport |
Andrey Grishel,
Tatiana Voinova |
source |
40 |
| SEUGI |
1997 |
Neural networks for business benefit |
Michael Kerin |
source |
20 |
| SEUGI |
1997 |
Point-and-click data validation using SAS/AF software |
Leif Puddefoot |
source |
9 |
| SEUGI |
1997 |
ROI in DW: a fast return on investment in data warehousing |
Jim Davis,
Thomas J. R. Emmerich |
source |
42 |
| PharmaSUG |
1997 |
How Do I Take the Mean of an Apple and an Orange? Techniques for Integrating Data from Multiple Studies |
Linda Collins |
|
8 |
| SUGI |
1997 |
"How to Save $30,000 in 4 Hours "-Migrating SAS Systems from the Mainframe to the PC |
Iain Robertson |
source |
5 |
| SUGI |
1997 |
Creating UNIX Network Usage Charts and Displaying Them on an Intranet |
Stephen B. Taubman,
David Kelly |
source |
4 |
| SUGI |
1997 |
Quantitation of Interactive Effects between Anticancer Agents Using SAS Macros and SAS/GRAPH |
Yalan Wang,
Jun Zuo,
M. Guill. Wientjes |
source |
6 |
| SCSUG |
1996 |
SAS and the Year 2000 Problem |
Clarence W. Jackson |
|
10 |
| SCSUG |
1996 |
SAS System Programming Tips and Efficiencies: A Tutorial |
Andrew H. Karp |
|
8 |
| NESUG |
1996 |
A Data Warehous/Business Intelligence Facility: Success in an Insurance Company |
John Gilbert |
|
10 |
| NESUG |
1996 |
Quick & Easy SAS/AF Applications Using SAS/ASSIST Software, SAS Data Views, Block Menus and HTML |
Jeanne M. Spicer |
|
6 |
| WUSS |
1996 |
In-House SAS Training |
Martin Haase |
source |
6 |
| WUSS |
1996 |
SAS System Programming Tips and Efficiencies: A Tutorial |
Andrew H. Karp |
source |
8 |
| WUSS |
1996 |
Warehouse Now! The Legacy Uncovered |
Jay A. Jaffe |
source |
6 |
| PNWSUG |
1996 |
Using SAS View to Enhance Software Quality, Improve Data Security and Reduce Data Replication |
Adam Hendricks |
|
27 |
| PNWSUG |
1996 |
When and How th PROC TABULATE Can Be Used |
Minghui Yang |
|
10 |
| SEUGI |
1996 |
A Practical Application of a SAS Data Warehouse in Clinical Trial Reporting |
Christine Smith,
David Smith |
source |
6 |
| SEUGI |
1996 |
Early quality assessment in data warehouse loading |
Jan Wilem van der Grijp |
source |
13 |
| SEUGI |
1996 |
Implementing a datawarehouse in the existing infrastructure of a bank - A case study |
Robert van Gemert |
source |
16 |
| SUGI |
1996 |
Advanced DATA Step Topics and Tips |
Neil H. Howard,
Cynthia L. Zender |
source |
|
| SUGI |
1996 |
Quick and Easy AF Applications Using SAS/ASSIST Software, SAS Data Views, Block Menus and HTML |
Jeanne M. Spicer |
source |
6 |
| SUGI |
1996 |
SELECT ITEMS FROM PROC.SQL WHERE ITEMS > BASICS |
Alan Dickson,
Ray Pass |
source |
10 |
| SCSUG |
1995 |
Building a Graphical Network Analysis System Using SAS/EIS |
Mahdi Al-Haery |
|
7 |
| MWSUG |
1995 |
A Historical Perspective of SAS's Future |
Rick Nicola |
|
5 |
| NESUG |
1995 |
A Creative Way to Read Stored Printed Reports Using the INPUT Statement and PROC TRANSPOSE |
Karen E. Davis |
|
2 |
| NESUG |
1995 |
SELECT ITEMS FROM PROC.SQL WHERE ITEMS > BASICS |
Alan Dickson,
Ray Pass |
|
10 |
| NESUG |
1995 |
Working with SAS Date and Time Functions |
Andrew H. Karp |
|
5 |
| SESUG |
1995 |
SELECT ITEMS FROM PROC.SQL WHERE ITEMS > BASICS |
Alan Dickson,
Ray Pass |
|
10 |
| SESUG |
1995 |
The Elements of SAS Programming Style |
Frank C. Dilorio,
Jean Cocteau |
|
6 |
| SESUG |
1995 |
Working with SAS Date and Time Functions |
Andrew H. Karp |
|
5 |
| SEUGI |
1995 |
A Concept on Data Delivery for Large Enterprisewide Information Systems |
Stephan Tobler |
source |
14 |
| SEUGI |
1995 |
A Mainframe Based System for Data Exchange Between Various Application Systems an Different Platforms |
Michael Fehringer,
Norbeert Semmelbauer |
source |
10 |
| SEUGI |
1995 |
A Way to Handle Pharmacokinetic Studies with SAS Software |
Jean-Michel Cardot |
source |
8 |
| SEUGI |
1995 |
An Introduction to SAS/CPE Software |
Julin Ginevro |
source |
25 |
| SEUGI |
1995 |
Early Experiences Using the SAS/CPE Software |
Allan McBain |
source |
4 |
| SEUGI |
1995 |
Transforming and Presenting Information From Raw Data to an Organized Document Through the SAS System Version 6.08 for Windows Features |
Paola Balardi |
source |
11 |
| SUGI |
1995 |
Controlling Sealed-Source Inventories Using the FRAME Entry in SAS/ AF Software |
Ralph Royce |
source |
6 |
| SCSUG |
1994 |
Creating 'Variable Name' Data Sets with CALL VNAME and PROC TRANSPOSE |
David Swift |
|
8 |
| SCSUG |
1994 |
Exploring Data Using Base SAS Software |
Thomas J. Winn Jr. |
|
6 |
| WUSS |
1994 |
ROBOSAS: Laboratory Automation and SAS |
Charles R. Villarrubia,
Seth Michelson,
Ronald Rhodes,
Edward Leung |
source |
7 |
| WUSS |
1994 |
Working with SAS Date and Time Functions |
Andrew H. Karp |
source |
5 |
| WUSS |
1994 |
Writing SAS Programs that Work |
Susan J. Slaughter,
Lora D. Delwiche |
source |
6 |
| MWSUG |
1994 |
SAS: The Complete Solution for Medical Data Analysis |
Diane E. Brown |
|
10 |
| SEUGI |
1994 |
To run an EIS Project Within the Public Health and Medical Sector |
Jan-Olov Isaksson |
source |
9 |
| SEUGI |
1994 |
Using the SAS System to Show Traffic Load in a Mobile Telephone Network |
Mikael D. Aagaard |
source |
14 |
| SUGI |
1994 |
A Macro to Associate Time-Oriented Data From Two Independent Sources |
David Arnold |
source |
5 |
| SUGI |
1994 |
A SAS/AF System for Entry, Validation, Analysis, and Reporting of Diverse Survey Data from Multiple Sites |
William A. Harris,
Charles W. Warren |
source |
6 |
| SUGI |
1994 |
Exploring Data With Base SAS Software |
Thomas J. Winn Jr. |
source |
6 |
| SUGI |
1994 |
Report Production System-"Report Line " |
Samuel Berestizhevsky,
Tanya Kolosova |
source |
4 |
| SUGI |
1994 |
You Want to Analyze All of the Oil Production Data for 90% of Canada Using the SAS System for PCs? You Gotta Be Kidding! |
Ned Etris,
Mark Bercov |
source |
6 |
| SCSUG |
1993 |
Exploring Data Using Base SAS Software |
Thomas J. Winn Jr. |
|
30 |
| MWSUG |
1993 |
Data Integrity Validation - Proactive vs. Reactive |
Douglas P. DeYoung |
|
6 |
| SUGI |
1993 |
Beyond Column Input: Advanced Techniques with the INFILE and INPUT Statements |
Kathy McLeod,
Nancy Mae Bonney |
source |
10 |
| SUGI |
1993 |
Cars, Dogs, and Drivers: Working with Large "Public "Data Sets |
Joseph E. St. Sauver |
source |
|
| SUGI |
1993 |
Data Compression and the SAS System |
Philip Bardsley |
source |
6 |
| SUGI |
1993 |
Enhancing Data Entry Screens for the Processing of "The Directory of Texas Manufacturers "Using SAS Screen Control Language, SAS/AF, and SAS/FSP |
Betty Smith |
source |
6 |
| SUGI |
1993 |
Getting to Know You, Getting to Know All About You: Simple Techniques for Forming a Relationship with Your Data |
Arthur L. Carpenter |
source |
6 |
| SUGI |
1993 |
Putting the Pieces Together: Applying Advanced SAS Macro Techniques to Everyday Problems |
Jim C. Knoop |
source |
7 |
| SUGI |
1993 |
Spectral Decomposition and Reconstruction of Nuclear Plant Signals |
Kristin K. Hoyer,
Kenny C. Gross |
source |
6 |
| SUGI |
1993 |
The FlLEVAR Option: A Tool for Management of Large Numbers of Raw Data Files |
Henry W. Buffum,
Jeffrey S. Rosen,
Richard W. Latimer |
source |
4 |
| SUGI |
1993 |
Using the SAS System for Error Control in Clinical Trials Data'bas'es |
William C. Murphy,
Howard M. Proskin,
Gary B. Freeman |
source |
3 |
| SESUG |
1993 |
Space Saving Tools: Compression in SAS 6.07 |
Philip Bardsley |
|
9 |
| SCSUG |
1992 |
Graphical Analysis of Clinical Canceer Data Using SAS Macros and SAS/GRAPH |
Karen L. Knorr,
David G. Mascorro,
Greg S. Shaw,
Susan G. Hilsenbeck,
John J. Hough,
Gary M. Clark |
|
10 |
| SEUGI |
1992 |
Bipeptidic Matrix Clustering |
B. Pflugfelder,
E. Ferran |
source |
31 |
| SEUGI |
1992 |
Data Analysis and Storage Using the SAS System at JET, the Joint European Torus |
Knud Thomsen |
source |
16 |
| SUGI |
1992 |
CPU and DASD Impacts of Release 6.06 of the SAS System |
Michael J. Schilling |
source |
7 |
| SUGI |
1992 |
Performance Enhancements in SAS Procedures for Small and Large Applications |
Leigh A. Ihnen |
source |
10 |
| SUGI |
1992 |
Validation of the UPLOAD and DOWNLOAD Procedures in the SAS System |
Richard A. Markus,
Jeffrey S. Kouba,
Curt Snyder,
Louise Murphy |
source |
6 |
| NESUG |
1991 |
Fuzzy Merges (How to Make MERGE Really Work) |
Jack N. Shoemaker |
|
6 |
| SEUGI |
1991 |
Is EIS Easy? |
Jim Thomason |
source |
5 |
| SEUGI |
1991 |
Modelling the Development of a Professional Group in a Macroeconomic Environment - Exampole of Doctors in Austria |
Ulrike Radosch |
source |
11 |
| SEUGI |
1991 |
SAS/CPE Software for VMS |
Chris Starke |
source |
10 |
| SUGI |
1991 |
Computer Performance Evaluation Using SAS/CPE Software under VMS: A Case Study |
Virginia M. Dineley |
source |
11 |
| SUGI |
1991 |
SPAM: its Not Just for Sandwiches Anymore |
Standish Sibley |
source |
6 |
| SUGI |
1991 |
Toward a Unified Analysis Environment: Two Years Later |
Charles R. Villarrubia,
Greg Silva,
Bruce Ingraham,
Seth Michelson |
source |
4 |
| NESUG |
1990 |
Basics of the INPUT Statement |
Robert Virgile |
|
7 |
| NESUG |
1990 |
Efficiency Techniques for Improving I/O and Processing Time in the DATA Step |
Neil H. Howard |
|
9 |
| NESUG |
1990 |
Efficient SAS Software Programming: A New Synthesis |
Jean Hardy |
|
8 |
| SEUGI |
1990 |
Using the SAS System for Analysis of VMS Computer Performance Data |
Tony Fisher |
source |
5 |
| SUGI |
1990 |
Determining and Profiling MVS System Activity with MXG and SAS Software |
Paul J. Waldowski |
source |
6 |
| SUGI |
1990 |
Disk Inventory and Control System: A REXX Tool for the Management of SAS Databases under CMS |
Arthur L. Carpenter |
source |
6 |
| SUGI |
1990 |
Managing a Multiuser SAS Database with Version 6 SAS/AF Software: Generic Tasks |
Todd C. Folsom |
source |
4 |
| SUGI |
1990 |
SAS/GRAPH Software and Numerical Taxonomy |
Dan Jacobs |
source |
6 |
| SUGI |
1990 |
Using SAS/CPE Software for Analysis of VMS'"Computer Performance Data |
Tim Rowles |
source |
7 |
| NESUG |
1989 |
Efficiency Techniques for Improving I/O and Processing Time in the DATA Step |
Neil H. Howard |
|
6 |
| SEUGI |
1989 |
A SAS Procedure For Evaluating Inulin Clearance Data |
Norbert Gretz |
source |
10 |
| SUGI |
1989 |
A Meta-database Implementation Strategy for Documentation and Retrieval Using the SAS System |
John Podgurski |
source |
10 |
| SUGI |
1989 |
A Program to Calculate Weights for Specified Spectral Windows: A SPECTRA Procedure Application |
Tim Arnold,
Ed Fryar |
source |
2 |
| SUGI |
1989 |
A Test Scoring Procedure Using the SAS System |
Jean Hardy,
Charles Vachon |
source |
3 |
| SUGI |
1989 |
Codebooks and SAS DATA Steps Automated and Integrated with a SAS Program Generator |
Jim Green |
source |
6 |
| SUGI |
1989 |
Enhancing the Visual Impact and Clarity of Graphics Output Using the Customizing Power of the Annotate = Data Set |
Karen Lacy Helsel |
source |
6 |
| SUGI |
1989 |
Harvesting Information: Data Cleanup and Analysis Techniques |
Gary F. Plazyk |
source |
6 |
| SUGI |
1989 |
Keeping Data Integrity in Large Corporations |
Martin J. Godkin |
source |
4 |
| SUGI |
1989 |
SAS Tutorial Session: Reading and Writing Data to External Files |
Ronald P. Cody |
source |
|
| SUGI |
1989 |
Writing Portable SAS Programs |
Sally J. Painter |
source |
3 |
| NESUG |
1988 |
Efficiency Techniques for Improving I/O and Processing Time in the DATA Step |
Neil H. Howard |
|
14 |
| SUGI |
1988 |
An Integrated Clinical Data Management System at Allergan, Inc. |
Jeffrey S. Kouba |
source |
4 |
| SUGI |
1988 |
Application of CHESMAP-An Environmental Data Mapping Program |
Dan Jacobs,
David G. Swartz |
source |
9 |
| SUGI |
1988 |
Cutting Costs in the DATA Step: Efficiency Techniques for Improving I/O and Processing Time |
Neil H. Howard |
source |
6 |
| SUGI |
1988 |
Effective Use of Custom Report Writing Tools |
Craig Dickstein |
source |
6 |
| SUGI |
1988 |
Efficient Programming with the SAS System for Personal Computers: Save Time, Save Space |
Lisa Ann Horwitz,
E. Tim Thompson |
source |
6 |
| SUGI |
1988 |
Menu-driven Statistical Defect Analysis System |
Ed Jurgensen,
Tom Lorman,
Tom Pineo |
source |
5 |
| SUGI |
1988 |
Subgrouping and Subsetting before Invoking the SHEWHART Procedure |
Mark A. Soboslai |
source |
6 |
| SUGI |
1988 |
The Nuts and Bolts of Course Development |
Jean Ussery |
source |
7 |
| SUGI |
1987 |
A Codebook Template for the Creation and Use of Permanent SAS Data Sets and Format Libraries (CMS Applications) |
John Podgurski |
source |
7 |
| SUGI |
1987 |
CARS - A Synergy of SAS Software, COBOL, and Data Analyzer for Health Care Reporting |
Kelly Tate,
Jim Woods |
source |
5 |
| SUGI |
1987 |
Controlling the SAS System and Its Users An Information System Tutorial |
Thomas R. Hoffman |
source |
5 |
| SUGI |
1987 |
Graphical Displays of Nonhierarchical Cluster Analysis Solutions |
John M. Larus |
source |
7 |
| SUGI |
1987 |
The SAS System for Personal Computers and Electronic Data Recorders at a Field Location |
Russell T. Graham,
Jonalea R. Tonn |
source |
3 |
| SEUGI |
1986 |
Principal Component Methods for Classification of Groups of Samples |
Peter Yendle,
Richard Brereton,
Simon Badham |
source |
34 |
| SUGI |
1985 |
Development of a Data Management System for Long-term Ecological Research |
Marvin F. Marozas,
Robert A. McLaughlin,
William K. Michener |
source |
6 |
| SUGI |
1985 |
Non parametric Sequential Trend Test |
Young C. Park |
source |
5 |
| SUGI |
1985 |
On Migrating a SAS-based Data Base to a Production System |
Thomas G. Kryzak |
source |
3 |
| SUGI |
1985 |
RAGS: An Interactive SAS, IDMS, and FORTRAN Tool for Regression Analysis |
Brent L. Peterson |
source |
5 |
| SEUGI |
1984 |
Progression of Chronic Renal Failure |
M. Strauch,
N. Gretz |
source |
8 |
| SUGI |
1984 |
A SAS Testscoring and Item Analysis Program Which Utilizes the SAS Macro Facility |
Charles E. Rich |
source |
6 |
| SUGI |
1984 |
A System for the Storage and Retrieval of Citations and the Generation of Bibliographies |
Erika Mares Stone |
source |
6 |
| SUGI |
1984 |
Interactive Psychological Testing Using the SAS System: A SAS Program to Administer and Score the MMPI |
Joseph M. Antonello,
Robert M. Hamer |
source |
5 |
| SUGI |
1984 |
New SAS Tools for Data Base Management |
N. D. Prabhakar |
source |
3 |
| SUGI |
1984 |
SAS Execution Panels for Users |
William R. Greenwood |
source |
5 |
| SEUGI |
1983 |
CMS/SAS VS. VMAP at General Accident |
Robert Davidson |
|
3 |
| SUGI |
1983 |
A SAS Program for the Extended Mantel-Haenszel Procedure |
Alan C. Fisher,
Daniel M. Wildman |
source |
6 |
| SUGI |
1983 |
Saving the Best for Last? First? In the Middle? Alternative Approaches to Teaching SAS and Beginning Data Processing |
David H. Christiansen,
James D. Hosking |
source |
4 |
| SUGI |
1983 |
Teaching SAS as a First Computer Language |
Jean Ussery |
source |
4 |
| SUGI |
1983 |
Transferring and Processing a "Very Large "Data Set from a PDP 11/34 to an IBM 360/370 |
Keith E. Muller,
Kathleen J. Seiple |
source |
6 |
| SUGI |
1983 |
Using SAS with a DBMS to Form a Versatile Information System |
Stephen M. Smith |
source |
6 |
| SUGI |
1982 |
ASPP: Automated SAS Program Producer |
Theresa J. Hart,
David A. Pyne |
source |
4 |
| SUGI |
1982 |
Management of SAS Based Data Analysis |
Wm. Ford Calhoun,
James Holt |
source |
4 |
| SUGI |
1982 |
The Role of the Departmental Consultant in the Computer Center |
Eileen Driscoll |
source |
3 |
| SUGI |
1982 |
Using CMS Exec Files for Data Management and Report Generation |
J.R. Barrett,
G. Blum |
source |
4 |
| SUGI |
1979 |
Project Control System |
Susan E. Bengtson,
Byron C. Lewis,
Richard Nelson |
source |
3 |
| SUGI |
1979 |
SAS in a Course for Beginning Computer Users |
Philip N. Gallagher Jr. |
source |
3 |
| SUGI |
1978 |
A SAS-Based Small-Area Profile System: Its Use in Primary Care Resource Development |
Edward M. Bosanac |
source |
6 |
| SUGI |
1978 |
Interfacing a Mumps-Based Data Entry System to SAS |
Joel F. Achtenberg,
J. Philip Miller |
source |
7 |
| SUGI |
1978 |
KRUWALC, A Macro for Categorical Data |
Donald J. Henderson |
source |
5 |
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