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651 papers and 55 presentations; 649 titles.

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Conference × Year × Title × Authors Extras Pages
WUSS 2026 Demystifying Regression Analysis Techniques with R Zheyuan Yu,
Kirk Paul Lafler,
Zichun Gao,
Jiaxin Xu,
Zeqi Li,
Ruochen Shao		 35
WUSS 2026 SQL Everywhere! Reuse your PROC SQL Code in R and Python with DuckDB Matthew T. Slaughter,
Isaiah Lankham,
Kirk Paul Lafler		 source 19
PharmaSUG CN 2026 Efficient Strategies for Handling Data Issues in Clinical Trial Submissions Kate Sun source 7
PharmaSUG CN 2026 Exploring the Architecture of Statistical Programming Languages in the AI Era Jiang Chao,
Wang Li,
Wang Juan,
Su Ya,
Yan Na		 source 8
PharmaSUG 2026 Regression Analysis Made Easy Using R Zheyuan Yu,
Kirk Paul Lafler,
Zichun Gao,
Jiaxin Xu,
Zeqi Li,
Ruochen Shao		 source 32
PHUSE US 2026 Check Yourself: Edit Checks and Queries Made Easy with Shiny Maya Gans source
presentation source		 8
PHUSE US 2026 Data Diaries Don't Lie: Stats That Spot ePRO Risks Steven A. Gilbert,
Nechama Katan		 source
presentation source		 12
PHUSE US 2026 Orchestrating Multi-Agent Workflows for Complex Trial Data Integration Rajesh Hagalwadi source 8
PHUSE US 2026 Trends in eSub Evaluation Findings: A Twenty-Year Perspective on Data Traceability Lisa Kaye Brooks source
presentation source		 9
PHUSE US 2026 Validation Strategies for Agentic AI Platforms in GxP-Regulated Clinical Data Environments Rajesh Hagalwadi source
presentation source		 9
PHUSE APAC 2026 Advancing Clinical Trial Analysis with Trimmed Means: Estimands, Intercurrent Events, and Regulatory Alignment Prasanth Palanisamy source
presentation source		 9
PHUSE APAC 2026 AI for Adverse Event Signal Detection: Moving Beyond Monika Monika source
presentation source		 10
PHUSE APAC 2026 AI-Driven RBQM: Bridging Operational Excellence and Global Regulatory Demands Hyoback Lee,
Sailesh Bajpai		 source
presentation source		 4
PHUSE APAC 2026 Critical & Sensitive Information (CSI) Paper AS02 Revolutionizing Clinical Quality: A Frontier Approach with Quality by Design (QbD), Infrastructure Modernization and Data-Driven Analytics Priti Gupta,
Deepa Balaji		 source
presentation source		 12
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 Information to Insights: Harnessing Centralized Monitoring in RBQM to proactively identify and mitigate risks in Clinical Trials Bismita Borkakoty,
Priyangshu Chowdhury		 source
presentation source		 12
PHUSE APAC 2026 How Central Statistical Monitoring Drives a Risk-Based Approach to Clinical Trial Monitoring Charles Warne source
presentation source		 9
PHUSE APAC 2026 Quantum-Proofing Patient Safety: A Post-Quantum and LLM-Powered Pilot for IoMT Resilience Arthi Rajendran source
presentation source		 11
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 Solving the Fragmentation Challenge in RA Trials: Deriving deeper insights Umayal Annamalai,
KiranKumar Vyas		 source
presentation source		 13
PHUSE EU 2025 Check Yourself: Edit Checks and Queries Made Easy with Shiny [presentation] Kirsty R. Lauderdale,
Maya Gans		 source 10
PHUSE EU 2025 Collaborative Industry Open-Source Solutions for Clinical Trial Quality Management Björn Koneswarakantha,
Frederik Collin		 source
presentation source		 9
PHUSE EU 2025 Keeping it Real: A Tiered Approach to Real-World Data Quality by Leveraging Synthetic Data Lisa Murch,
William Kuan		 source
presentation source		 10
PHUSE EU 2025 No Patients? No Problem Define Your Study Data with Python at the CORE John McDade source
presentation source		 11
PHUSE EU 2025 Visualising the Invisible: Patient Journey with Waterfall, Spider and Swimmer Plots Varsha Mithun Patil,
Sunita Poojary		 source
presentation source		 14
PHUSE EU 2025 Why Wait for Real Data? The Power of Synthetic Data in Modern Clinical Trials Abhijeet Arora source
presentation source		 6
MWSUG 2025 Multivariate Ratio Edits Using Tolerance Intervals [presentation] Daniel Tuyisenge,
Derek Young,
Thomas Mathew		 source 26
SESUG 2025 Data Diagnostics with Base SAS Mark L. Jordan 38
PharmaSUG 2025 Debugging Options in R: Applications and Usage in Clinical Programming Madhusudhan Ginnaram,
Bingjun Wang,
Jeetender Chauhan,
Sarad Nepal		 source 6
PharmaSUG 2025 Efficient Strategies for Handling Data Issues in Clinical Trial Submissions Kate Sun source 7
PharmaSUG 2025 Enhance Safety Data Analysis Using SafetyGraphic R Package Vicky Yuan source 17
PharmaSUG 2025 Leveraging Python for Statistical Analysis in Public Health: Techniques and Visualizations for Life Sciences Professionals Michael Carnival source 14
PharmaSUG 2025 Navigating the transition of legacy processes for SDTM creation Jyothi Ketavarapu source 5
PharmaSUG 2025 Sensitivity Analysis for Overall Survival Binal Mehta,
Patel Mukesh		 source 13
PHUSE US 2025 Evaluation of Open-Source Technologies in Clinical Trial Reporting Jaimin Patel source
poster source		 7
PHUSE US 2025 Leadership Presentations: Turning Disruption into Opportunity - Guiding Teams Through AI-Powered Transformation [presentation] Li Zheng source 20
PHUSE US 2025 Predictive Analytics for Adverse Event Underreporting Steven A. Gilbert source
presentation source		 10
PHUSE US 2025 Risk Based Quality Management (RBQM) in Clinical Data Management Marcin Kot,
Anna Górecka		 source
presentation source		 9
PHUSE US 2025 The Olympics of Data Ingestions Cathryn Herbst source
presentation source		 8
PHUSE US 2025 The Right Tool for the Job: Enhancing Risk-Based Monitoring and Data Cleaning Casey Higgins source
presentation source		 4
PHUSE US 2025 Transforming Clinical Trials with AI-Driven Protocol Optimization and Next-Gen Statistical Programming Ravindra Shukla source
presentation source		 8
PHUSE US 2025 Visualising Longitudinal Patients' Responses in a Clinical Study: A Unified Graphical Approach Avani Reddy Alla,
Sunil Kumar Pusarla		 source
poster source		 6
PHUSE EU 2024 Artificial Intelligence Potential Use Cases in Clinical Data Engineering Deepak Pakalapati,
Mounika Pillamarapu		 source
presentation source		 8
PHUSE EU 2024 Bootstrap Simulation for Outlier Detection in Operational Site Metrics Using Patient Reassignment Björn Koneswarakantha source
presentation source		 3
SESUG 2024 Data Diagnostics with Base SAS Mark L. Jordan source 37
SESUG 2024 Introduction to Clustering Algorithms Jason Brinkley source 10
SESUG 2024 Who's Bringing That Big Data Energy? A 47-Year Longitudinal Analysis of 30,000 Presentations in the SAS User Community To Elucidate Top Contributors and Rising Stars Troy Martin Hughes source 36
WUSS 2024 Regression Analysis Made Easy Using SAS Studio Zheyuan (Walter) Yu source 42
PharmaSUG 2024 Visual discovery in Risk-Based Monitoring using topological models Kostiantyn Drach,
Iryna Kotenko		 source 31
PHUSE US 2024 Automation of Exploratory Report Generation using R shiny and R Markdown Denny Sebastian source
poster source		 7
PHUSE US 2024 Beyond Outliers: Unsupervised Anomaly Detection in Clinical Trial Data Helena Yaben,
Kian Norouzi		 source
presentation source		 9
PHUSE US 2024 Beyond the Hype: A Pragmatic Approach to Leveraging AI/ML for Data Review Robert Musterer source
presentation source		 10
PHUSE US 2024 Collaborative Development of a Clinical Trial Data Anomaly Detection Tool within an Industry Consortium Pekka Tiikkainen source
presentation source		 6
PHUSE US 2024 Data Designer: Empowering data mapping, manipulation and analysis for advanced insights and decision making Mukul K Mittal source
presentation source		 6
PHUSE US 2024 Identifying Data Quality Issues in Clinical Trials Using OpenAI Embeddings Yash Shah,
Ashwin Rai		 source
presentation source		 5
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 Redefining 'Interactive' Dashboards to Enhance Safety Data Review Andrew McGowan source
presentation source		 7
PHUSE US 2024 Synergising Large Language Models (LLMs) and Human-in-the-Loop (HITL) for Data Noise Reduction in the RBQM Approach Mukesh Babu,
Vineet Jain		 source
presentation source		 7
PHUSE US 2024 Utilising Machine Learning Algorithms to Detect the Outlier or Inconsistencies in the Analysis Results in Datasets and Summary Reports Weiwei Xu,
Linshan Yuan		 source
poster source		 5
PHUSE EU 2023 Figures are Basic(ally Overlooked) Kaleb Mead source
poster source		 17
PHUSE EU 2023 Risk-Based Monitoring in Clinical Trials with Machine-Learning-Powered Anomaly Detection Zaid Al-Jubouri,
Ece Kavalci		 source
presentation source		 11
WUSS 2023 Introduction to Machine Learning - Descriptions and Best Practices Jim Box source 13
WUSS 2023 Regression Analysis Made Easy Using SAS Studio Kirk Paul Lafler,
Zheyuan (Walter) Yu,
Nuoer Lu,
Nicklas (Rebel) Yee,
Yanzhang Gavin Chen,
Kai Kang		 source 43
WUSS 2023 Univariate Outlier Detection Using SAS Fan Yang source 12
WUSS 2023 Who's Bringing That Big Data Energy? A 47-Year Longitudinal Analysis of 30,000 Presentations in the SAS User Community To Elucidate Top Contributors and Rising Stars Troy Martin Hughes source 36
SESUG 2023 Regression Analysis Made Easy Using SAS Studio Kirk Paul Lafler,
Zheyuan (Walter) Yu,
Nuoer Lu,
Daniel Qian,
Kai Kang,
Yanzhang Gavin Chen,
Nicklas (Rebel) Yee,
Yixuan (Jason) Xiang		 source 43
PharmaSUG 2023 What is Machine Learning, anyway? Jim Box source 11
PHUSE US 2023 Friends Don't Let Friends Make Ugly Dashboards [presentation] Marcia Powers,
Deidre Kreifels		 source
video		 14
PHUSE US 2023 Snow White & the 7 Keys for Data Lake Hydration [presentation] Chris Decker,
Kate McMahon		 source
video		 23
PHUSE US 2023 The Thick and Thin of Adopting Risk-Based Approach to Data Management [presentation] Michał Ruciński source
video		 17
PHUSE EU 2022 Exploratory Analysis - People-powered Pathways to Success within a Critical Risk-based Approach [presentation] Simon Jackson source
video		 21
PHUSE EU 2022 Finding Anomalies and Outliers in Clinical Trial Time Series Data Pekka Tiikkainen source
presentation source		 6
PHUSE EU 2022 Interactive Data Visualisation for Faster and Improved Data Insights [presentation] Markus Niederstrasser source
video		 38
PHUSE EU 2022 Processing Data and Documents with Natural Language Processing and Quantitative Anonymisation Strategies in Support of CTIS Disclosure Requirements [presentation] Elliot Zimmerman,
John Lyons		 source
video		 25
PHUSE EU 2022 Python to Automate an AR Project Identifying Discrepancies across Fields from a Government Open-source Dataset of COVID-19 Vaccine Registrations Aldir Medeiros Filho source
video
presentation source		 14
PHUSE EU 2022 RBM Beyond the Mandate: The Importance and Impacts of Risk-based Monitoring Today [presentation] Gina Wood,
Alison Banda		 source 14
SAS Explore 2022 Leveraging KT Charts with Streaming Data [video] Byron Biggs,
Sergiy Peredriy		 source
youtube
SAS Explore 2022 SAS Intelligent Monitoring: Anomaly Detection App in the Azure Marketplace [video] Saurabh Mishra source
PHUSE US 2022 Advancing RBQM Strategy with Enterprise-level Quality Risk Analytics, NLP/AI, and Immersive Technologies [presentation] Vera Pomerantseva source 20
PHUSE US 2022 Choosing Your Tile: Quick Clinical Data Summary Visualizations using SAS Enterprise Guide 7.1 Graph Tasks (Tile Charts) Amber Frazier source
presentation source		 4
PHUSE US 2022 The Decentralized Trials Data Problem: Foundations for the Future of Clinical Trials [presentation] Raj Indupuri source
video		 11
PHUSE EU 2021 Does No Errors Equal High Quality? [presentation] Julie Solbjerg Appel,
Sanna Herrgård		 source
video		 23
PHUSE EU 2021 EMA Panel Discussion: What Might the Future Landscape of Submitting Data Look Like in 2025 ? [presentation] Eftychia-Eirini Psarelli,
Jesper Kjær		 source 21
PHUSE EU 2021 Increasing Utility of Anonymised Data - Improved Banding Techniques [presentation] Jasper Enderman source
video		 14
PHUSE US 2021 Next Evolution Step(s) for Statistical Programmers: "Clinical Data Scientist" or "Clinical Data Analytics Engineer"? [presentation] Amar Mahidadia,
Sascha Ahrweiler		 source
video		 16
PHUSE US 2021 Real-Time Clinical Trial Analytics Using Automation with IBM Clinical, Medidata Rave and Datacise [presentation] Aditya Gadiko,
Christopher C. Hurley		 source
video		 7
PHUSE US 2021 Visualizations to Support DSMB Monitoring [presentation] Derek Coombs source
video		 14
PharmaSUG 2021 A Lead Programmer-s Guide to a Successful Submission Pranav Soanker,
Santosh Shivakavi		 source 8
PharmaSUG 2021 Build a model: Introducing a methodology to develop multiple regression models using R in oncology trial analyses Girish Kankipati,
Jai Deep Mittapalli		 source 20
PharmaSUG 2021 Making Your SAS Results More Meaningful with Color Kirk Paul Lafler source 19
PharmaSUG 2021 Preserving the Privacy of Participant's Data by Data Anonymization Chaithanya Velupam,
Kaushik Sundaram		 source 10
PharmaSUG 2021 Visualization of Sparse PK Concentration Sampling Data, Step by Step (Improvement by Improvement) Ilya Krivelevich,
Simon Lin		 source 14
PHUSE EU 2020 Analysis Used in RBM [presentation] Aminul Islam,
Shafi Chowdhury		 source
video		 8
PHUSE EU 2020 Catch Them When You Can ... Fix Them [presentation] Anna Panasenko source
video		 23
PHUSE EU 2020 Template-based Graph Generation in Python and its Maintenance in Git [presentation] Pournima Prabhakaran source
video		 21
SESUG 2020 Making Your SAS Results More Meaningful with Color Kirk Paul Lafler source 20
SESUG 2020 Outlier Detection and Treatment Ross Bettinger source 29
SGF 2020 Automation in SAS Visual Data Mining and Machine Learning Wendy Czika source 26
SGF 2020 From Santiago to the Spirit Lake Nation: 30 Things I Learned in 30 Years as a Statistical Consultant AnnMaria De Mars source 20
SGF 2020 Scalable Cloud-Based Time Series Analysis and Forecasting Using Open Source Software Javier Delgado source 21
SGF 2020 Solving the VAST Challenge: Three Case Studies Using SAS Visual Analytics Riley Benson source 17
SGF 2020 The Seven Most Popular Machine Learning Algorithms for Online Fraud Detection and Their Use in SAS Patrick Maher source 6
PHUSE US 2020 2020 Syneos Health. All rights reserved Working Smarter source 7
PHUSE US 2020 A Real-world View of Cataracts Jeffrey Headd,
Walter Cedeno		 source
presentation source		 11
PHUSE EU 2019 A Data-driven and cost-effective approach towards Risk Based Monitoring Vineet Jain source
presentation source		 7
PHUSE EU 2019 Finding the Right Balance - Data Management Surveillance in a Fully Outsourced Partnership Model Konstanze Morgenroth source
presentation source		 11
PHUSE EU 2019 Laboratory Data: Issues with Myultiple Reference Ranges and Methods of Normalisation Jessica Hoegg,
Laura Marquis		 source
presentation source		 20
PHUSE EU 2019 SMART RPA - powered by Machine Learning Charan Kumar Kuyyamudira Janardhana source
presentation source		 10
SESUG 2019 A Random Forest Example of the Boston Housing Data using the Base SAS and the PROC_R macro in SAS Enterprise Guide Melvin T. Alexander source 18
SESUG 2019 Analyzing Hospital Medicare Cost Report Data Using SAS - Updated with Output Kimberly Andrews source 19
SESUG 2019 Making Your SAS Results More Meaningful with Color Kirk Paul Lafler source 20
SESUG 2019 Probability Plots for Exploratory Data Analysis Dennis J. Beal,
Oak Ridge		 source 8
SESUG 2019 The Best of Both Worlds: Forecasting Using Time Series with Inputs David A. Dickey source 19
SESUG 2019 The Gender Gap in the Education System Geoffrey Dean source 14
SESUG 2019 Using PROC FCMP to Implement Anomaly Detection Method Tsung-Hsun Tsai source 6
SCSUG 2019 Explore your data before you rush to analysis, you will thank me later: explorations in cross section data Steven C. Myers source 28
SCSUG 2019 Making Your SAS Results More Meaningful with Color Kirk Paul Lafler source 20
SCSUG 2019 Working with Customer Contact Data Jon Purvis source 9
MWSUG 2019 Explore your data before you rush to analysis, you will thank me later: explorations in cross section data Steven C. Myers 28
MWSUG 2019 Profiling hospital length of stay using the mode Anne Cain-Nielsen,
Scott Regenbogen		 1
WUSS 2019 A strategy for speed Dating YuTing Tian source 21
PharmaSUG 2019 An Introduction to the Process of Improving a Neural Network YuTing Tian source 22
PharmaSUG 2019 Logistic and Linear Regression Assumptions: Violation Recognition and Control Deanna Naomi Schreiber-Gregory,
Karlen Bader		 source 21
SGF 2019 An Introduction to the Process of Improving a Neural Network YuTing Tian source 22
SGF 2019 Data Governance: Harder, Better, Faster, Stronger Vincent Rejany source 18
SGF 2019 Detecting Fraud and Other Anomalies Using Isolation Forests Ryan Gillespie source 6
SGF 2019 Factors Influencing Academic Performance Onkar Mayekar,
Miriam McGaugh		 source 9
SGF 2019 Playing Favorites: Our Top 10 Model Studio Features in SAS Visual Data Mining and Machine Learning Wendy Czika,
Peter Gerakios		 source 16
SGF 2019 Statistical Data Checks to Identify Questionable and Suspicious Data Kaitie Lawson source 11
SGF 2019 SWAT's it all about? SAS Viya for Python Users Carrie Foreman source 18
SGF 2019 The Best of Both Worlds: Forecasting Using Time Series with Inputs David A. Dickey source 19
SGF 2019 Unsupervised Learning for Anomaly Detection in Securities Data Laura Rudolphi,
Chris A. Robinson		 source 7
SGF 2019 Using ETS Software for Intervention Models for Sales of Cars Anders Milhøj source 8
PHUSE US 2019 An Open Clinical Data Quality Framework Vineet Jain source
presentation source		 11
PHUSE US 2019 How to Take the Risk Out of Risk-based Monitoring Shafi Chowdhury,
Nurahamid Siddiki		 source
presentation source		 4
SCSUG 2018 Making Your SAS Results, Reports, Tables, Charts and Spreadsheets More Meaningful with Color Kirk Paul Lafler source 20
PHUSE EU 2018 Collinearity in Mixed Models John Hendrickx source
presentation source		 11
PHUSE EU 2018 Implementing Advanced Analytics and Machine Learning in Risk-based Strategies Rajneesh Patil source
presentation source		 3
SESUG 2018 Analyzing Hospital Medicare Cost Report Data Using SAS Kimberly Andrews source 19
SESUG 2018 Forecasting: Something Old, Something New David A. Dickey source 26
SESUG 2018 Logistic and Linear Regression Assumptions: Violation Recognition and Control Deanna Naomi Schreiber-Gregory,
Henry M. Jackson		 source 22
MWSUG 2018 An Introduction to the Process of Improving a Neural Network YuTing Tian 22
MWSUG 2018 Logistic and Linear Regression Assumptions: Violation Recognition and Control Deanna Naomi Schreiber-Gregory,
Karlen Bader		 22
MWSUG 2018 Making Your SAS Output, Results, Reports, Charts and Spreadsheets More Meaningful with Color Kirk Paul Lafler 20
WUSS 2018 Forecasting tourist's arrivals to the USA with SARIMA models. Mostafa Zahedjahromi source 9
WUSS 2018 Forecasting: Something Old, Something New David A. Dickey source 26
WUSS 2018 How sensitive is your analysis? A case study on addressing it at ADaM level. Bhargav Koduru,
Balavenkata Pitchuka		 source 7
WUSS 2018 Logistic and Linear Regression Assumptions: Violation Recognition and Control Deanna Naomi Schreiber-Gregory source 21
WUSS 2018 Making Your SAS Results, Reports, Tables, Charts and Spreadsheets More Meaningful with Color Kirk Paul Lafler source 20
PHUSE US 2018 Assuring Data Integrity and Data Quality in Sponsor Submissions Paul Schuette source
presentation source		 5
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 Programmers are from Mars and Statisticians are from Venus Shweta Padmanaban,
Sangeetha Sathaiah		 source
presentation source		 6
PHUSE US 2018 Row Row Row of Zeroes: Their Significance in Summary Tables and Subgroup Analyses Sridhar Vijendra,
Sumanth Horabail		 source
presentation source		 6
PharmaSUG 2018 Using JMP Scripting Language (JSL) to create an application interface for automated analysis of Lab Data in Clinical Trial Dongsun Cao source 11
SGF 2018 A Cautionary Tale of Using Machine Learning within Credit Risk in the Utilities Industry Spiros Potamitis,
Paul Malley		 source 8
SGF 2018 Analytics of Things: New Analytical Models for Creating Business Value from IoT Data Ryan Gillespie source 11
SGF 2018 Back to Basics: Get Better Insights from Data Atrin Assa source 10
SGF 2018 Credit Score: A Comparison of Gradient Boosting with Logistic Regression in Practical Cases Paulo Di Cellio Dias,
Marc Witarsa		 source 25
SGF 2018 Distribution Circuit Load Forecasting Using Advanced Metering Infrastructure Data Prasenjit Shil,
Tom Anderson		 source 12
SGF 2018 Forecasting: Something Old, Something New David A. Dickey source 26
SGF 2018 Fraudsters Love Digital : An Emerging Threat Missed on Many Insurers Digitization Roadmaps David Hartley source 5
SGF 2018 Getting More Insight into Your Forecast Errors with the GLMSELECT and QUANTSELECT Procedures Gerhard Svolba source 26
SGF 2018 How to Use Streaming Analytics to Create a Real-Time Digital Twin Bradley W. Klenz source 14
SGF 2018 Innovating Government Decision-Making through Analytics Steve Bennett source 19
SGF 2018 New Frontiers in Pricing Analytics [presentation] Sharat Mathur source 22
SGF 2018 Robust Principal Component Analysis: Two Analyses in One Anthony Salis,
Zohreh Asgharzadeh,
Kyungduck Cha		 source 11
SGF 2018 SAS Visual Investigator and SAS Visual Analytics: Bridging the Gap between Subject Matter Experts Emily Chapman-Mcquiston source 12
SGF 2018 Scalable Cloud-Based Time Series Analysis and Forecasting Thiago Quirino,
Michael J. Leonard,
Ed Blair		 source 22
SGF 2018 To Catch a Thief: The Use of Analytics for Employee Fraud Detection [presentation] Bruce Bedford source 21
SGF 2018 Using the LIFETEST Procedure to Calculate an Alternative to Strike Rate in Limited Overs Cricket [presentation] Keith G. Curtis source 5
SESUG 2017 Data Quality Control: Using High Performance Binning to Prevent Information Loss Deanna Naomi Schreiber-Gregory,
Henry M. Jackson		 source 9
SESUG 2017 Detecting Outlying Data in Proficiency Studies with SAS Stacey Slone source 11
SESUG 2017 Missing Data and Complex Sample Surveys Using SAS: The Impact of Listwise Deletion vs. Multiple Imputation Methods on Point and Interval Estimates when Data are MCAR, MAR, and MNAR Listwise Deletion source 26
SESUG 2017 Using SAS to Employ Propensity Score Matching in an Institutional Research Office to Create Matched Groups for Outcomes Analyses Bobbie E. Frye,
James E. Bartlett		 source 19
SCSUG 2017 The True Price for Your House Mettilda Kaimathuruth,
Goutam Chakraborty		 source 15
PHUSE EU 2017 Data Cleaning Technique for Business Analytics: What Stats Van Do for DM Adam Korczynski source
presentation source		 16
PHUSE EU 2017 EXPLORT: A Shiny App to EXPLORE Data Interactively and EXPORT the Customised Graphics as an R Script Claire Petry source 5
PHUSE EU 2017 The Art of Data Visualization: DetectingMultivariate Data Outliers Using an Interactive Approach Diane Peers source
presentation source		 9
PharmaSUG 2017 Bird-s eye view of the data, a graphical exploration! Hrideep Antony source 9
PharmaSUG 2017 Laboratory Data Standardization with SAS Charley Z. Wu,
Dona-Lyn Wales		 source 12
SGF 2017 A SAS Macro for Covariate Specification in Linear, Logistic, and Survival Regression Sai Liu source
zip		 19
SGF 2017 Adding a Workflow to Your Analytics with SAS Visual Investigator Gordon Robinson,
Ryan Schmiedl		 source 10
SGF 2017 Analyzing Residuals in a PROC SURVEYLOGISTIC Model Bogdan Gadidov source 8
SGF 2017 Automate Validation of CDISC SDTM with SAS Sy J. Truong source 11
SGF 2017 Differentiate Effects from the Noise of Promotional Marketing Campaigns Alex Glushkovsky,
Matthew Fabian		 source 9
SGF 2017 Diving Deep into ODS Graphics Styles Dan Heath source 19
SGF 2017 How to Use SAS to Filter Stock for Trade Brian Shen source 9
SGF 2017 Identifying Abnormal Equipment Behavior and Filtering Data near the Edge for IoT Applications Ryan Gillespie,
Saurabh Gupta		 source 5
SGF 2017 Outline Outliers: Adding a Business Sense Alex Glushkovsky source 17
SGF 2017 Production Forecasting in the Age of Big Data in the Oil and Gas Industry [presentation] Vipin Prakash Gupta,
Satyajit Dwivedi		 source 17
SGF 2017 Revenue Score: Forecasting Credit Card Products with Zero Inflated Beta Regression and Gradient Boosting Marc Witarsa,
Paulo Di Cellio Dias		 source 20
SGF 2017 The Effects of Socioeconomic, Demographic Variables on US Mortality Using SAS Visual Analytics Catherine Loveless-Schmitt source
pdf		 22
SGF 2017 Timing is Everything: Detecting Important Behavior Triggers Daymond Ling source 12
SESUG 2016 Geospatial Analysis with PROC GMAP Michael Jadoo source 19
SESUG 2016 Make the Jump from Business User to Data Analyst in SAS Visual Analytics Ryan Kumpfmilller source 13
PHUSE EU 2016 encapsia - Providing Real-time, Interactive Visualisations of Clinical Data [presentation] Jon Carter source 9
MWSUG 2016 Regression Analysis of the Levels of Chlorine in the Public Water Supply in Orange County, FL Drew Doyle 11
PharmaSUG CN 2016 Clip Extreme Values for a More Readable Box Plot Mary Rose Sibayan,
Thea Arianna Valerio		 7
WUSS 2016 Best Practices in Machine Learning Applications Brett Wujek source 23
PharmaSUG 2016 "I Want the Mean, But not That One!" David W. Franklin source 5
PharmaSUG 2016 Data Visualization for Quality Control in NONMEM Data set Linghui Zhang source 9
PharmaSUG 2016 Elevate your Graphics Game: Violin Plots Spencer Childress source 9
PharmaSUG 2016 Empowering Users By Creating Data Visualization Applications In R/Shiny Sudhir Singh,
Brian Munneke,
Amulya R. Bista,
Jeff Cai		 source 8
PharmaSUG 2016 Handling Interim and Incomplete Data in a Clinical Trials Setting Paul Stutzman source 13
PharmaSUG 2016 Waterfall plot: two different approaches, one beautiful graph Ting Ma source 9
SGF 2016 An Analysis of Medicare Provider Utilization and Payment Data: A Focus on the Top 5 DRGs and Mental Health Care Joo Ann Lee,
Micheal Friendly,
Cathy Labrish		 source 28
SGF 2016 Best Practices for Machine Learning Applications Brett Wujek,
Funda Güneş,
Patrick Hall		 source 23
SGF 2016 Breakthroughs at Old Dominion Electric Cooperative with Energy Load Forecasting Innovation David Hamilton,
Steve Becker,
Emily Forney		 source 19
SGF 2016 Case Study Using SAS Forecast Studio: Daily Taxi Data from New York City [presentation] Simon Sheather source 47
SGF 2016 Customer Lifetime Value Modeling Vadim Pliner source
presentation		 4
SGF 2016 Evolving Fraud Types: Can Your Application Keep Up? Gordon Robinson source 11
SGF 2016 Medicare Fraud Analytics Using Cluster Analysis: How PROC FASTCLUS Can Refine the Identification of Peer Comparison Groups Paulo Macedo source
zip		 9
SGF 2016 Minimizing Fraud Risk through Dynamic Entity Resolution and Network Analysis Danielle Davis,
Stephen Boyd,
Ray Ong		 source 10
SGF 2016 Outlier Detection Using the Forward Search in SAS/IML Studio Jos Polfliet source
zip		 12
SGF 2016 Predicting the Current Market Value of a Housing Unit across the Four Census Regions of the United States Using SAS Enterprise Miner 12.3 Mostakim Tanjil,
Goutam Chakraborty		 source
presentation		 12
SGF 2016 Similarity Analysis: an Introduction, a Process, and a Supernova David J. Corliss source 11
SGF 2016 Transforming Data to Information in Education: Stop with the Point-and-Click!!! Sean W. Mulvenon source 9
MWSUG 2015 Let SAS Cleanse Your Dirty Data Kaushal Chaudhary,
Deanna Naomi Schreiber-Gregory		 13
MWSUG 2015 Slice and Dice your customers easily by using SAS Clustering Procedures Yanping Shen 9
PHUSE EU 2015 Efficient Data Reviews and Quality in Clinical Trials Using CDISC Data Standards Valérie Nedbal source 11
PHUSE EU 2015 Ensuring the Quality of your Data in Respiratory Trials: DM from a Statistical Standpoint Diana Stuart,
Abigail Fuller		 source
presentation source		 5
PHUSE EU 2015 Programming Strategically for PK/PD Data Grace Lu source
presentation source		 8
SESUG 2015 How to Build Study Quality Surveillance for a Clinical Study? Angela Teng source 3
SESUG 2015 Predictive Modeling Using SAS Visual Statistics: Beyond the Prediction Xiangiang Meng,
Wayne Thompson,
Jennifer Ames		 source 12
SESUG 2015 Regression Analysis of the Levels of Chlorine in the Public Water Supply in Orange County, FL Drew Doyle source 10
WUSS 2015 Graphical Results in Clinical Studies A focus on graphics used in oncology Nora Ruel,
Paul Frankel		 source 12
WUSS 2015 Yes, PROC FREQ does that! AnnMaria De Mars source 15
PharmaSUG CN 2015 SAS End-to-End solutions in Clinical Trial Emma Liu 17
PharmaSUG 2015 Leveraging ADaM Principles to Make Analysis Database and Table Programming More Efficient Andrew L Hulme source 13
SGF 2015 Analyzing Messy and Wide Data on a Desktop John P. Sall source 4
SGF 2015 Analyzing Parking Meter Transactions Using SAS Procedures Anders Milhøj source 12
SGF 2015 Forecasting Vehicle Sharing Demand Using SAS Forecast Studio Kushal Kathed,
Goutam Chakraborty,
Ayush Priyadarshi		 source 9
SGF 2015 Operations Integration, Audits, and Performance Analysis: Getting the Most Out of SAS Environment Manager Bob Bonham,
Bryan Ellington		 source 16
SGF 2015 Predictive Modeling Using SAS Visual Statistics: Beyond the Prediction Xiangxiang Meng,
Jennifer Ames,
Wayne Thompson		 source 12
SGF 2015 SAS Does Data Science: How to Succeed in a Data Science Competition Patrick Hall source
zip		 11
SGF 2015 Survey Sample Designs for Auditing, Fraud, and Forensics. Turner Bond source 13
SGF 2015 Take a Bite Out of Crime with SAS Visual Scenario Designer Yue Qi source 10
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 Using SAS/STAT Software to Implement a Multivariate Aadaptive Outlier Detection Approach to Distinguish Outliers from Extreme Values Paulo Macedo source 12
SESUG 2014 Expanding the Use of Weight of Evidence and Information Value to Continuous Dependent Variables for Variable Reduction and Scorecard Development Alec Zhixiao Lin,
Tung-Ying Hsieh		 23
SESUG 2014 Using SAS/STAT to implement a multivariate adaptive outlier detection approach to distinguish outliers from extreme values Paulo Macedo source 11
PHUSE EU 2014 Monitoring Clinical Trials with a SAS Risk-Based Approach Laurie Rose source
presentation source		 9
PHUSE EU 2014 Population Segmentation in a Healthcare Environment MaryAnne DePesquo source
presentation source		 5
PHUSE EU 2014 Risk based monitoring using integrated clinical development platform Authors Sita Rama Swamy Peddiboyina,
Shailesh Vijay Joshi		 source
presentation source		 9
MWSUG 2014 PROC SQL for DATA Step Die-Hards Christianna S. Williams 22
MWSUG 2014 Should more of your PROC REGS be QUANTREGs and ROBUSTREGs? Peter L. Flom 17
PharmaSUG 2014 Healthcare Data Manipulation and Analytics Using SAS Lumin Shen,
Jane Lu		 source 11
PharmaSUG 2014 Let SAS Improve Your CDISC Data Quality Wayne (Weizhen) Zhong source 12
PharmaSUG 2014 Risk-Based Monitoring of Clinical Trials Using JMP Clinical Richard C. Zink,
Kelci J. Miclaus		 source 15
PharmaSUG 2014 That SASsy Lab Data Amie Bissonett source 6
SGF 2014 A SAS Macro to Diagnose Influential Subjects in Longitudinal Studies Grant Schneider,
Randy Tobias		 source
zip		 18
SGF 2014 An Intermediate Primer to Estimating Linear Multilevel Models Using SAS PROC MIXED Bethany A. Bell,
Whitney Smiley,
Mihaela Ene,
Genine L. Blue		 source 19
SGF 2014 Application of Survey Sampling for Quality Control Yi Du source 8
SGF 2014 Big Data Analysis for Resource-Constrained Surgical Scheduling Elizabeth Rowse,
Paul Harper		 source 5
SGF 2014 Case-Level Residual Analysis in the CALIS Procedure Catherine Truxillo source 17
SGF 2014 CMS Core Measures, the Affordable Care Act, and SAS Visual Analytics Joe Whitehurst,
Diane Hatcher		 source 16
SGF 2014 Combined SAS ODS Graphics Procedures with ODS to Create Graphs of Individual Data Howard Liang source 6
SGF 2014 Customer Profiling for Marketing Strategies in a Healthcare Environment MaryAnne DePesquo source 7
SGF 2014 Healthcare Services Data Distribution, Transformation, and Model Fitting Dawit Mulugeta,
Jason Greenfield,
Tison Bolen,
Lisa Conley		 source 22
SGF 2014 Making It Happen: A Novel Way to Combine, Construct, Customize, and Implement Your Big Data with a SAS Data Discovery, Analytics, and Fraud Framework in Medicare Vivek Sethunatesan source 15
SGF 2014 Risk-Based Monitoring of Clinical Trials Using JMP Clinical Richard C. Zink source 14
SGF 2014 SAS Visual Analytics Deliverers Insights into the UK University League Tables Richard Self,
Stuart Berry,
Claire Foyle,
Dave Voorhis		 source 4
SGF 2014 Selecting Peer Institutions with Cluster Analysis Diana D. Suhr source 12
SGF 2014 The Desert and the Dunes: Finding Oases and Avoiding Mirages with the SAS Visual Analytics Explorer Nascif Abousalh-Neto source 15
SGF 2014 The Use of Analytics for Insurance Claim Fraud Detection: A Unique Challenge Roosevelt Mosley,
Nick Kucera		 source 15
SGF 2014 Using PROC GPLOT and PROC REG Together to Make One Great Graph William 'Gui' Zupko II source 14
WUSS 2013 Telling Stories with Your Data - Graphs, Tables and Basic, Basic Statistics with SAS Enterprise Guide AnnMaria De Mars source 19
PHUSE EU 2013 Central Statistical Monitoring in Action Francois Torche,
Erik Doffagne		 source 6
PHUSE EU 2013 Determination of Body Sway area by Fourier Analysis of its Contour Thomas Wollseifen source
presentation source		 7
PHUSE EU 2013 Statistics: The Fourth Dimension of a "Statistical Programmer" Gauri Khatu,
Vibhavari Inamadar		 source 12
PHUSE EU 2013 Visual Approaches for Safety Analysis and Review of Clinical Trials [presentation] Valérie Nedbal source 34
MWSUG 2013 Introduction to REDCap for Clinical Data Collection Shannon M. Morrison 17
NESUG 2013 An Animated Guide: An Introduction to Neural Nets: Russell M. Lavery 12
NESUG 2013 Understanding the outliers in healthcare expenditure data Gandhi Bhattarai 15
PharmaSUG 2013 Dances with Box Plot Xuefeng Yu source 9
PharmaSUG 2013 Defensive Programming and Error-handling: The Path Less Travelled Tracy Sherman,
Angela S. Ringelberg		 source 9
SGF 2013 Be Customer Wise or Otherwise: Combining Data Mining and Interactive Visual Analytics to Analyze Large and Complex Customer Resource Management (CRM) Data Aditya Misra,
Junyao Ji,
Kam Tin Seong		 source 11
SGF 2013 Data Fitness: A SAS Macro-based Application for Data Quality of Large Health Administrative Data Mahmoud Azimaee source 12
SGF 2013 Do SAS users read books? Using SAS graphics to enhance survey research Barbara B. Okerson source 10
SGF 2013 Introducing and Producing Thunderstorm or Rain-drop Scatter Plots Using the SAS/GRAPH Annotate Facility Charlie Liu source 13
SGF 2013 Next-Generation Detection Engine for Fraud and Compliance Ryan Schmiedl source 6
SGF 2013 Product Affinity Segmentation That Uses the Doughnut Clustering Approach Darius S. Baer,
Goutam Chakraborty		 source 17
SGF 2013 Regression of NASCAR: Looking into Five Years of Jimmie Johnson Alex Herrington,
Liuchun Yang,
Yun Gao		 source 20
SGF 2013 Segmentation and Classification Analysis Using SAS Rachel Poulsen source 14
SGF 2013 The Forest and the Trees: See It All with SAS Visual Analytics Explorer Nascif Abousalh-Neto source 14
NESUG 2012 PROC SQL for DATA Step Die-Hards Christianna S. Williams 20
SCSUG 2012 Dirty Data? Clean it up with SAS. Gabriela Cantu source 11
SESUG 2012 Do SAS users read books? Using SAS graphics to enhance survey research Barbara B. Okerson source 10
SESUG 2012 How to Perform and Interpret Chi-Square and T-Tests Jennifer L. Waller source 14
SESUG 2012 Sample Size Determination for a Nonparametric Upper Tolerance Limit for any Order Statistic Dennis J. Beal source 8
MWSUG 2012 A Brief Survey of Clustering and Segmentation for Customer Intelligence George J. Hurley 18
MWSUG 2012 An Analysis of Diabetes Risk Factors Using Data Mining Approach Akkarapol Sa-ngasoongsong,
Jongsawas Chongwatpol		 11
WUSS 2012 A SAS Macro for Displaying Institutional Risk-Adjusted Performance: Forest vs. Funnel Plots Zhongmin Li,
Geeta Mahendra		 source 13
WUSS 2012 Multivariate Statistical Analysis in SAS: Segmentation and Classification of BehavioralData Rachel Poulsen source 14
WUSS 2012 PROC BOXPLOT - Using the CLIP FACTOR option to produce more readable figures Heidi Nasizadeh Sangart,
Michelle Wang		 source 5
WUSS 2012 The Steps to Follow in a Multiple Regression Analysis Theresa H. Ngo source 12
WUSS 2012 Visualizing Data Techniques, Including Autocharting and Big Data Justin Choy source 12
PharmaSUG 2012 Reporting Outliers in Data: A Macro to Identify and Report Distant Data Points Howard Liang,
Jason Bishop		 source 5
PharmaSUG 2012 Taming the Box Plot Sanjiv Ramalingam source 7
SGF 2012 Community Detection to Identify Fraud Events in Telecommunications Networks Carlos Andre R. Pinheiro source 8
SGF 2012 Comparison of K-Means, Normal Mixtures and Probabilistic-D Clustering for B2B Segmentation Using Customers Perceptions Satish Garla,
Gary Gaeth,
Goutam Chakraborty		 source 8
SGF 2012 CSI: Customer Segmentation Intelligence for Increasing Profits Darius S. Baer source 13
SGF 2012 How to Perform and Interpret Chi-Square and T-Tests Jennifer L. Waller source 20
SGF 2012 Let Oil and Gas Talk to You: Predicting Production Performance Keith R. Holdaway source 12
SGF 2012 Making Exploration of Nonlinear Models Fast and Easy Using JMP 10 Don McCormack source 8
SGF 2012 Physician Practice Pattern Variation: Using Data Mining and Predictive Modeling to Identify and Control Costly Treatment Patterns David C. Ogden source 12
SGF 2012 The Steps to Follow in a Multiple Regression Analysis Theresa H. Ngo source 12
SGF 2012 The Traveling Salesman Problem: Optimizing Delivery Routes Using Genetic Algorithms Sabah Sadiq source 6
SGF 2012 Trend Analysis: An Automated Data Quality Approach for Large Health Administrative Databases Mahmoud Azimaee source 9
SCSUG 2011 Statistical comparison of relative proportions of bacterial genetic sequences Jose F Garcia-Mazcorro source 19
SESUG 2011 Healthcare Provider Cost Reporting Information System Kimberly Andrews,
Richard Andrews		 source 19
SESUG 2011 Using PROC GPLOT and PROC REG Together to Make One Great Graph William 'Gui' Zupko II source 14
WUSS 2011 Comparison of K-Means, Normal Mixtures and Probabilistic-D Clustering for B2B Segmentation Using Customers Perceptions Satish Garla source 9
WUSS 2011 SAS Essentials III: Statistics for Hamsters AnnMaria De Mars source 18
WUSS 2011 SAS Macros for the Working Statistician William Krebs source 9
PHUSE EU 2011 Data cleaning and spotting outliers with UNIVARIATE Michael Auld source
presentation source		 6
MWSUG 2011 Data Quality Review for Missing Values and Outliers Ying Guo,
Bradford J. Danner		 9
MWSUG 2011 Outlier resistance of multivariate bioequivalence procedures Srinand P. Nandakumar,
Joseph W. McKean		 13
NESUG 2011 PROC SQL for DATA Step Die-Hards Christianna S. Williams 22
PharmaSUG 2011 Clinical Trials Versus Health Outcomes Research: SAS/STAT Versus SAS Enterprise Miner Patricia B. Cerrito source 15
PharmaSUG 2011 Data Quality Review for Missing Values and Outliers Ying Guo,
Bradford J. Danner		 source 8
SGF 2011 Detecting and Preventing Fraud in Financial Institutions Ellen Joyner source 16
SGF 2011 Eliminating Response Style Segments in Survey Data via Double Standardization before Clustering Murali Krishna Pagolu,
Goutam Chakraborty		 source 15
SGF 2011 Highlighting Unusual Behavior in Insurance Based on Social Network Analysis Carlos Andre R. Pinheiro source 9
SGF 2011 Marketing Investment Optimization Framework for AmEx Travelers Cheques, Clustering Consumer Behavior Leveraging SAS/ETS to Uncover Investment Opportunities in an Environment Demanding Quick Decisions Landon Starr,
Pieter van Ispelen		 source 11
SGF 2011 Present Graph Text-Based Components Using SAS 9.2 Graph Template Language (GTL) Zhuoye Xu source 19
SGF 2011 Time Series Data Mining with SAS Enterprise Miner Sascha Schubert,
Taiyeong Lee		 source 12
SGF 2011 Why Government Can Take the Lead in Fighting Fraud, and Use the SAS Fraud Framework to Get There Carl Hammersburg source 8
NESUG 2010 A SAS Application to Identify and Evaluate Outliers Richard Hendra,
Paulette W. Staum		 16
WUSS 2010 Rediscovering SAS/IML Software: Modern Data Analysis for the Practicing Statistician Rick Wicklin source 18
WUSS 2010 Statistical Analysis - The First Steps Jennifer L. Waller source 20
PHUSE EU 2010 Assesment of Cox Proportional Hazard Model Adequacy Using PROC PHREG and PROC GPLOT Jadwiga Borucka source
presentation source		 13
PHUSE EU 2010 Useful Tips for Analysis of Variance (ANOVA) in Multicentre, Placebo Controlled Clinical Trials Joanna Romaniuk source
presentation source		 12
MWSUG 2010 JMP Simulation-Based Empirical Determination of Robust Scale Estimator and Comparison of Outlier Discrimination Performance Gennadiy Gorelik,
Tarun Chandra		 8
MWSUG 2010 Visualization with JMP - The Overlay, Spinning, Surface, and Contour Plots Mark Anawis 20
SESUG 2010 %RESTRUCT - SAS macro with Proc Univariate Milorad Stojanovic source 7
SESUG 2010 Detecting Medicaid Data Anomalies Using Data Mining Techniques Shenjun Zhu,
Qiling Shi,
Aran Canes		 source 9
SESUG 2010 Statistical Analysis - The First Steps Jennifer L. Waller source 20
PharmaSUG 2010 Physician Practice Pattern Variation: Using Data Mining and Predictive Modeling to Identify and Control Costly Treatment Patterns David C. Ogden 12
SGF 2010 A Picture Is Worth a Thousand Words: Integrated Visualization of Clinical Data Vikash Jain source 10
SGF 2010 Beyond the SAS Credit Risk Management Solution: The Gruppo Banca Carige Credit Monitoring Model and the Keinavo Advanced Web 2.0 Reporting Framework Johann Kerdal,
Francesco Marelli,
Fulvia Costone,
Danilo L. Perucchio		 source 10
SGF 2010 dATa qWaliti 4 Analytics David Barkaway,
Gerhard Svolba		 source 12
SGF 2010 Detecting Claim Fraud and Improving Product Quality: Case Studies in Reducing Warranty Costs David Froning source 8
SGF 2010 Fundamental Diagnostics for Two-Level Mixed Models: The SAS Macro MIXED_DX Bethany A. Bell,
Jason A. Schoeneberger,
Grant B. Morgan,
Jeffrey D. Kromrey,
John M. Ferron		 source 12
SGF 2010 Improving the Defense Lines: The Future of Fraud Detection in the Insurance Industry (with Fraud Risk Models, Text Mining, and Social Networks) Terisa Roberts source 7
SGF 2010 Physician Practice Pattern Variation: Using Data Mining and Predictive Modeling to Identify and Control Costly Treatment Patterns David C. Ogden source 12
SGF 2010 Rediscovering SAS/IML Software: Modern Data Analysis for the Practicing Statistician Rick Wicklin source 18
SGF 2010 Using the SAS System and SAS Enterprise Miner for Data Mining: A Study of Cancer Survival at the Mayo Clinic Leonard Gordon source 6
SCSUG 2009 SVD Filtered Temporal Usage Pattern Analysis and Clustering Liang Xie 12
SESUG 2009 A Little Stats Won't Hurt You Nathaniel Derby source 18
SESUG 2009 Constructing Baseline of Customer's Hourly Electric Usage in SAS Yuqing Xiao,
Bob Bolen,
Diane Cunningham,
Jiaying Xu		 source 7
SESUG 2009 Export Customized Graphs Directly into Microsoft Word Using Dynamic Data Exchange Dennis J. Beal source 11
SESUG 2009 MIXED_DX: A SAS Macro for Two-Level Linear Model Diagnostics Bethany A. Bell,
Grant B. Morgan,
Jason A. Schoeneberger,
John M. Ferron,
Jeffrey D. Kromrey		 source 17
PHUSE EU 2009 Clinical Database acceptance: what statistical review checks are necessary to validate a database? Genevieve Jehl source 12
PHUSE EU 2009 Zooming in on graphics Armin Gemperli source
presentation source		 7
MWSUG 2009 A Little Stats Won't Hurt You Nathaniel Derby 18
MWSUG 2009 Handy Procedures to Expand Your Analytics Skill Set Mary F. MacDougall 9
PNWSUG 2009 A Little Stats Won't Hurt You Nathaniel Derby 18
PNWSUG 2009 Building Multiple Linear Regression Models - Food for Thought Colleen E. McGahan,
Mei Chong		 11
NESUG 2009 A Picture Is Worth a Thousand Words: Integrated Visualization of Clinical Data Vikash Jain 10
NESUG 2009 Health Status and Attitudes Towards Health in Medical Expenditure Panel Survey (MEPS) Sample Population Pramit A. Nadpara 7
NESUG 2009 PROC SQL for DATA Step Die-Hards Christianna S. Williams 19
NESUG 2009 Taming the Box Plot Sanjiv Ramalingam 7
WUSS 2009 A Little Stats Won't Hurt You Nathaniel Derby source 18
WUSS 2009 Discriminant Analysis, a Powerful Classification Technique in Predictive Modeling George C. J. Fernandez source 20
WUSS 2009 Don't Be Loopy: Re-Sampling and Simulation the SAS Way David L. Cassell source 18
WUSS 2009 Modeling Spatial and Temporal Variations of Arsenic in Surface Water Anpalaki J. Ragavan source 10
WUSS 2009 Using SAS for Nonparametric Statistics Gerry Hobbs source 7
PharmaSUG 2009 A Little Stats Won't Hurt You Nathaniel Derby 18
PharmaSUG 2009 Customizing Your Own Box Plot Wenjie Wang,
Jade Huang		 7
PharmaSUG 2009 Detection of Multiple Outliers in UNIVARIATE Data Sets Marek K. Solak 7
PharmaSUG 2009 Don't Be Loopy: Re-Sampling and Simulation the SAS Way David L. Cassell 18
SGF 2009 A Little Stats Won't Hurt You Nathaniel Derby source 17
SGF 2009 A SAS Macro for Adaptive Regression Modeling George J. Knafl source 9
SGF 2009 Interactive Outlier Review and Regression Analysis in SAS Stat Studio Robert Seffrin source 10
SGF 2009 The Problem of Regression Assumptions and the Use of Predictive Modeling Patricia B. Cerrito source 20
WUSS 2008 Evaluation of a Hospice Care Referral Program Using Cox Proportional Hazards Model Lida Gharibvand,
Daniel R. Jeske,
Solomon Liao		 source 16
SESUG 2008 Health Status and Attitudes Towards Health in Medical Expenditure Panel Survey (MEPS) Sample Population Pramit Nadpara source 6
SESUG 2008 Identifying and listing outliers without using PROC Format option Other=Invalid Ruben Chiflikyan source 12
SESUG 2008 Interactive Outlier Review and Regression Analysis in Stat Studio Robert Seffrin source 9
PHUSE EU 2008 Drug Safety Reporting - now and then David J. Garbutt source 23
MWSUG 2008 Chemical Informatics using JMP PowerMV and ChemModLab S. Stanley Young,
Thomas H. Burger,
Michael S. Lajiness,
Wolf-D. Ihlenfeldt		 40
MWSUG 2008 Classification of Breast Cancer Cells Using JMP Marie Gaudard 34
NESUG 2008 Early Detection of Epidemic Outbreaks and Financial Bubbles Using Autoregressive Models with Structural Changes Ernest S. Shtatland,
Timur Shtatland		 15
NESUG 2008 ODS Graphics Editor Sanjay N. Matange 9
PharmaSUG 2008 Detecting Incorrect P-values John Morrill 5
PharmaSUG 2008 Innovative Techniques and Tools to Detect Data Quality Problems Hong Qi,
Allan Glaser		 8
PharmaSUG 2008 Statistical Approach to Establishing Bioequivalence William F. McCarthy,
Nan Guo		 12
SGF 2008 Advanced Statistical and Graphical features of SAS PHREG Lida Gharibvand,
George C. J. Fernandez		 source 12
SGF 2008 Another Look at Low-Order Autoregressive Models in Early Detection of Epidemic Outbreaks and Explosive Behaviors in Economic and Financial Time Series Ernest S. Shtatland source 12
SGF 2008 Data Mining Application of Non-Linear Mixed Modeling in Water Quality Analysis Anpalaki J. Ragavan source 14
SGF 2008 How to Use SAS to Fit Multiple Logistic Regression Models Anpalaki J. Ragavan source 13
SGF 2008 ODS Graphics Editor Sanjay N. Matange source 9
SGF 2008 PROC SQL for DATA Step Die-Hards Christianna S. Williams source 17
SGF 2008 Range Formats Made Easy A CreateRangeFormat Custom Task for SAS Enterprise Guide Petr Hustak source 9
SGF 2008 Technology Solutions to Detect Fraud and Counter Other IT Risks Eckhardt Kriel source 12
SGF 2008 Understanding Your Customer: Segmentation Techniques for Gaining Customer Insight and Predicting Risk in the Telecom Industry Glendon Cross,
Wayne Thompson		 source 14
SGF 2008 Use of Text Mining to Predict Patient Compliance Christiana Petrou source 15
SGF 2008 Using Regression Diagnostics and Clustering Criteria to Uncover ID Errors David J. Pasta,
Eric P. Elkin,
Rory Michaelis		 source 10
NESUG 2007 Selecting the Appropriate Outlier Detection Technique for Common Industry Applications Kunal Tiwari,
Krishna Mehta,
Nitin Jain,
Ramandeep Tiwari,
Gaurav Kanda		 5
SESUG 2007 Cleaning Data the Chauvenet Way Lily Lin,
San Mateo		 source 11
MWSUG 2007 Best Practices for Managing Predictive Models in a Production Environment Robert Chu 10
WUSS 2007 Cleaning Data the Chauvenet Way Lily Lin,
Paul D. Sherman		 source 11
WUSS 2007 Don't Be Loopy: Re-Sampling and Simulation the SAS Way David L. Cassell source 18
WUSS 2007 Survival Analysis Plots Using SAS ODS Graphics Lida Gharibvand,
George C. J. Fernandez		 source 10
WUSS 2007 Using Regression Diagnostics and Clustering Criteria to Uncover ID Errors David J. Pasta,
Eric P. Elkin,
Rory Michaelis		 source 10
PHUSE EU 2007 Method Validation in a PAT Environment using a SAS EG Addin Robert Eric Huisden source 6
PNWSUG 2007 Don't Be Loopy: Re-Sampling and Simulation the SAS Way David L. Cassell 18
PNWSUG 2007 New SAS Statistical Software: Just Over the Horizon [presentation] Randy Tobias 48
PharmaSUG 2007 Implementing Worst Rank Imputation Using SAS Qian Wang,
Eric Qi		 10
PharmaSUG 2007 SAS Macros to Detect and Evaluate Statistical Outliers Marek K. Solak 8
SGF 2007 Best Practices for Managing Predictive Models in a Production Environment Robert Duling,
David M. Thompson,
Wayne Chu		 source 10
SGF 2007 Data Mining to Investigate the Prescribing of Medications Longitudinally Mussie A. Tesfamicael source 17
SGF 2007 Don't Be Loopy: Re-Sampling and Simulation the SAS Way David L. Cassell source 18
SGF 2007 Learning What You Didn't Know about Your Data Larry W. Douglass source 16
SGF 2007 Skewness, Multicollinearity, Heteroskedasticity - You Name It, Cost Data Have It! Solutions to Violations of Assumptions of the Ordinary Least Squares Regression Model Using SAS Leonor L. Ayyangar source 7
SGF 2007 Using ODS Styles with SAS/GRAPH Jeff Heath,
Dan Cartier		 source 8
SGF 2007 Using SAS PROC NLMIXED for Robust Regression Steven A. Chen,
Lingyun Gilbert		 source 9
MWSUG 2006 Checking Assumptions in the Cox Proportional Hazards Regression Model Brenda W Gillespie 70
MWSUG 2006 Using Biweights for Handling Outliers George W Dombi 9
SCSUG 2006 Data Mining at the Texas State Auditor's Office Thomas J. Winn Jr. 11
PHUSE EU 2006 A tour through PTOC ROBUSTREG Michael O'Kelly source 8
PHUSE EU 2006 Statistical Graphics and Reporting in Drug Development Michael O'Connell,
Sven Knudsen		 source 13
SESUG 2006 Graphics for Statistical Concepts and Data Display David A. Dickey source 19
SESUG 2006 PROC SQL for DATA Step Die-Hards Christianna S. Williams source 17
WUSS 2006 Easy Methods to Investigate Large Datasets Using ODS Graphics and New Features in SAS 9 Aimee Foreman,
Miriam G. Cisternas		 source 10
WUSS 2006 Multi-Dimensional Data Presentation Karl Glaser source 8
WUSS 2006 Skewness, Multicollinearity, Heteroskedasticity - You Name It, Cost Data Have It! Solutions to Violations of Assumptions of Ordinary Least Squares Regression Model Using SAS Leonor Ayyangar source 7
SUGI 2006 Application of Proc Discrim and Proc Logistic in Credit Risk Modeling Jin Li source 9
SUGI 2006 Data Profiling Using Base SAS Software: A Quick Approach to Understanding Your Data Susan J. Nowlin source 8
SUGI 2006 Fraud Detection - A Primer for SAS Programmers Thomas J. Winn Jr. source 6
SUGI 2006 Modeling Water Quality Trend in Long Term Time Series Anpalaki J. Ragavan,
George C. J. Fernandez		 source 10
SUGI 2006 The Value of Real-Time Scoring Technology Using SAS Young Chun Kim source 6
SUGI 2006 Using SAS for Statistical Modeling of Nutrient Removal and Water Quality Aspects from Constructed Wetlands Rupali Mohansingh,
George C. J. Fernandez,
Keith E. Dennett		 source 11
SESUG 2005 Clustering Analysis of Micro Array Data John Schwarz source 12
MWSUG 2005 Calculation Of Health Disparity Indices Using Data Mining And The SAS Bridge To ESRI Mussie A. Tesfamicael 9
MWSUG 2005 Mining Transactional And Time Series Data Michael J. Leonard 26
MWSUG 2005 Time Dependent Data Exploration And Preprocessing: Doing It All By SAS Joseph Twagilimana 10
NESUG 2005 Introduction to SAS Enterprise Guide 3.0 for Statistical Analysis Charles B. Hallahan,
Linda P. Atkinson		 20
NESUG 2005 PROC SQL for DATA Step Die-Hards Christianna S. Williams 20
NESUG 2005 Stretching the Bounds of SAS/GRAPH Software Michael S. Zdeb,
Robert E. Allison		 20
PharmaSUG 2005 A Single SAS Macro for Range Checking an Entire Database Kim Truett 7
PharmaSUG 2005 Using Proc Freq for Manageable Data Summarization Curtis Wolf 6
SUGI 2005 An Introduction to Quantile Regression and the QUANTREG Procedure Colin Chen source 24
SUGI 2005 Automating Predictive Analysis to Predict Medicare Fraud Christine L. Warner source 9
SUGI 2005 Data Profiling: Designing the Blueprint for Improved Data Quality Brett Dorr,
Pat M. Herbert		 source 10
SUGI 2005 Introduction to SAS Enterprise Guide 3.0 for Statistical Analysis Charles B. Hallahan,
Linda P. Atkinson		 source 20
SUGI 2005 Mining Transactional And Time Series Data Michael J. Leonard,
Brenda Wolfe		 source 26
SUGI 2005 Predicting Workers' Compensation Insurance Fraud Using SAS Enterprise Miner 5.1 and SAS Text Miner Terry J. Woodfield source 6
SUGI 2005 Stretching the Bounds of SAS/GRAPH Software Michael S. Zdeb,
Robert E. Allison		 source 20
NESUG 2004 Graphical Display of Data - A Nonparametric Approach Shi-Tao Yeh 18
NESUG 2004 Introduction to Using Enterprise Guide for Statistical Analysis Charles B. Hallahan,
Linda P. Atkinson		 19
NESUG 2004 Perusing, Choosing, and Not Mis-using: Non-parametric vs Parametric tests in SAS Venita DePuy,
Paul Pappas		 5
NESUG 2004 Using SAS at SAS: The Mining of SAS Technical Support Annette M. Sanders,
Craig DeVault		 22
SCSUG 2004 Fraud Detection - A Primer for SAS Programmers Thomas J. Winn Jr. 9
SESUG 2004 An Overview of Non-parametric Tests in SAS: When, Why, and How Paul A. Pappas,
Venita DePuy		 source 5
SESUG 2004 Mixed Model Influence Diagnostics Oliver Schabenberger source 17
SESUG 2004 Statistical Analysis of Gene Expression Micro Arrays John Schwarz source 8
SESUG 2004 Using SAS at SAS: The Mining of SAS Technical Support Annette M. Sanders,
Craig DeVault		 source 22
WUSS 2004 Is your picture worth a thousand words? Creating Effective Presentations with SAS/GRAPH Justina M. Flavin,
Arthur L. Carpenter		 source 13
WUSS 2004 Mixed Model Influence Diagnostics Oliver Schabenberger source 17
WUSS 2004 Using Proc Freq for Manageable Data Summarization Curtis Wolf source 5
MWSUG 2004 The Randomization Test Procedure: Testing for a Non-Zero Quadratic Effect Ling Huang,
Paul W. Johnson		 8
MWSUG 2004 Using SAS at SAS: The timing of SAS Tech Support Annette M. Sanders,
Craig DeVault		 22
PharmaSUG 2004 An Experiment with Experimental Proc RobustReg Shuang Lu 5
PharmaSUG 2004 Box plots and Radar Plots for Pharmaceutical Studies: Some of the Better Ways to get a Clear Picture of Study Results Mary Cowmeadow 8
SUGI 2004 Assessing Model Fit and Finding a Fit Model Margaret L. Bogle,
Rajiv Goel,
Robert M. Hamer,
Chan-Hee Jo,
Eric Siegel,
Pippa M. Simpson		 source 17
SUGI 2004 DATA: "Getting to Know You; Getting to Know All About You" Larry W. Douglass,
Sue E. Douglass		 source 17
SUGI 2004 How I Stopped Worrying and Learned to Love Pearsons p: Increasing Robustness in Correlation Analysis Eric M. Rosenberg source 11
SUGI 2004 Introduction to Using SAS Enterprise Guide for Statistical Analysis Charles B. Hallahan,
Linda P. Atkinson		 source 20
SUGI 2004 Mixed Model Influence Diagnostics Oliver Schabenberger source 18
SUGI 2004 SAS Macros are the Cure for Quality Control Pains Gary M. McQuown source 7
SUGI 2004 Using SAS at SAS: The Mining of SAS Technical Support Annette M. Sanders,
Craig DeVault		 source 23
WUSS 2003 Regression Diagnostic Plots George C. J. Fernandez source 9
WUSS 2003 Using SAS for Classical Item Analysis and Option Analysis Chong Ho Yu,
Josephine Wai-chi Wong		 source 6
SESUG 2003 An Analysis Tool for Reviewing Farm Economic Data Using SAS/AF Van Johnson source 7
SESUG 2003 Developing a Marketing Geographic Segmentation System Using SAS Software Kellie M. Poulin,
Allison N. Freeman		 source 10
SESUG 2003 SAS Macros are the Cure for Quality Control Pains Gary M. McQuown source 6
NESUG 2003 SAS Macros are the Cure for Quality Control Pains Gary M. McQuown 6
SEUGI 2003 Intelligence at the Heart of Retail [presentation] Chris Dunk source 38
SEUGI 2003 Optimizing Fraud Management Systems [presentation] Henrik Wagner,
Pushkar Bhat		 source 29
SEUGI 2003 Second-generation data warehouse - strategic and tactics at the Vilnius Bank [presentation] Laukai source 22
PharmaSUG 2003 Developing "EXSAS" an integrated system for statistical analysis of non-clinical experimental data using animals Chikuma Hamada 6
SUGI 2003 A Drill-Down Diet: An Example of a Dynamic Detail Access on the Web Using SAS/GRAPH and ODS Nadia Redmond source 4
SUGI 2003 Developing a Marketing Geographic Segmentation System Using SAS Software Allison N. Shubert-Freeman,
Kellie M. Poulin,
Shawn C. Yoder,
Michael R. Morgan,
Jennifer K. Warner		 source 6
SUGI 2003 Modeling Customer Lifetime Value Using Survival Analysis - An Application in the Telecommunications Industry Junxiang Lu source 6
SCSUG 2002 Geostatistical Tools in the SAS System E. Barry Moser 6
SCSUG 2002 Using the SAS System as an Audit Support Tool Thomas J. Winn Jr.,
Kirby L. Cossey,
Ernest Cuellar,
Olin Davis,
Dorvin Handrick,
Joyce Inman		 4
NESUG 2002 PROC SQL for DATA Step Die-Hards Christianna S. Williams 10
NESUG 2002 Testing 1,2,3: Determining Redundant Procedures in Product Testing Eric Rosenberg 12
SESUG 2002 Using PROC GREPLAY With ANNOTATE Data Sets for Effective Multi-Panel Graphics Walter T. Morgan source 12
WUSS 2002 An Overview of Remedial Tools for the Violation of Parametric Test Assumptions in the SAS System Chong Ho Yu source 6
WUSS 2002 Multiple Linear Regression Analysis of Total Mercury Levels in Blood and Urine Samples Miki Yamauchi,
George C. J. Fernandez,
Stanley Omaye		 source 6
WUSS 2002 Using SAS/IML to Create a Chi-squared Plot for Checking Normality Assumption in Multivariate Data Steven Hoff source 5
SEUGI 2002 Closing the loop on Fraud [presentation] Anton Hirschowitz source 27
SEUGI 2002 Introduction to Customer Intelligence [presentation] Alan Gormley source 26
SEUGI 2002 IT as a Driving Force for Business Innovation in Slovak Insurance [presentation] Oto Maly source 49
SEUGI 2002 Making Your Data a Strategic Asset [presentation] Tony Fisher source 29
SUGI 2002 Data Cleaning 101 Ronald P. Cody source 10
SUGI 2002 Discriminant Analysis, A Powerful Classification Technique in Data Mining George C. J. Fernandez source 9
SUGI 2002 Fast and Easy Ways to Annoy a Statistician: The Sharing and Presentation of Data Between a SAS Programmer and a Statistician Richard M. Mitchell source 10
SUGI 2002 Fast and Easy Ways to Check Your Work: Using PROC MEANS to Confirm Continuous Variable Categorizations Richard M. Mitchell source 2
SUGI 2002 Predicting Customer Churn in the Telecommunications Industry - An Application of Survival Analysis Modeling Using SAS Junxiang Lu source 6
SUGI 2002 Robust Regression and Outlier Detection with the ROBUSTREG Procedure Colin Chen source 13
MWSUG 2001 Seven (plus or minus two) Clusters, A Monte Carlo Study Larry Hoyle 10
NESUG 2001 Fast and Easy Ways to Annoy a Statistician: The Sharing and Presentation of Data Between a SAS Programmer and a Statistician Richard M. Mitchell 10
NESUG 2001 INVALID: a Data Review Macro Using PROC FORMAT Option OTHER=INVALID to Identify and List Outliers Ronald J. Fehd 9
NESUG 2001 The Marriage of EDA & Mapping Techniques for the Analysis/Display of Census Data. Dave L. DesJardins 8
NESUG 2001 Using Surveys to Understand the Present and Predict the Future Aliza Heching,
Ying Tat Leung		 6
VIEWS 2001 Knowledge Discovery and Data Mining Applied to Engineering Applications [presentation] Shirley Williams 22
VIEWS 2001 The Use of Enterprise Miner with Large Volumes of Data, for Forecasting in an Automated Batch Process [presentation] Matthew Glasson,
Justine Eastman		 17
WUSS 2001 Clean Your Data with PROC SQL Ann Olmsted source 5
WUSS 2001 Discriminant Analysis, A Powerful Classification Technique in Data Mining George C. J. Fernandez source 9
SESUG 2001 INVALID: a Data Review Macro Using PROC FORMAT Option OTHER=INVALID to Identify and List Outliers Ronald J. Fehd source 11
SCSUG 2001 INVALID: a Data Review Macro Using PROC FORMAT Option OTHER=INVALID to Identify and List Outliers Ronald J. Fehd 11
SEUGI 2001 Data Mining In a Zero Latency Enterprise [presentation] Philip Bosinoff source 36
SEUGI 2001 Fraud Detection in Healthcare - MBF's successful approach through SAS South Pacific Data Mining Discovery Centre [presentation] Jolie Reichel source 14
SEUGI 2001 Implentation of an outlier detection method for hihg throughput screening in drug discovery [presentation] Ronny Schrijvers,
Rudi Verbeeck		 source 23
SEUGI 2001 New Features and Future Directions for Enterprise Miner [presentation] David R. Duling,
Gerhard Held		 source 31
SEUGI 2001 Risk Simulation with SAS/IML - Corporate Insurance Solutions for Fortune 2000 companies [presentation] Boris Weimann,
Gero Niessen		 source 20
SEUGI 2001 Sales Force Management Through Intranet [presentation] Anna Surova,
Jan Maly,
Jaroslav Kafka		 source 21
SEUGI 2001 The Use of Enterprise Miner with Large Volumes of Data, for Forecasting in an Automated Batch Process [presentation] Justine Eastman source 12
PharmaSUG 2001 Automatic Estimation of Dixon's Test for Extreme Values Using a SAS Macro Driven Program Don (Dongguang) Li,
Edmond Edwards		 4
SUGI 2001 Data Cleaning 101 Ronald P. Cody source 10
SUGI 2001 Fast and Easy Ways to Annoy a Statistician: The Sharing and Presentation of Data Between a SAS Programmer and a Statistician Richard M. Mitchell source 10
SUGI 2001 Outliers, Inliers, and Just Plain Liars - New Graphical EDA+ Techniques For Understanding Data Dave L. DesJardins source 6
SUGI 2001 Predictive Modeling in the Insurance Industry Using SAS Terry J. Woodfield source 5
SCSUG 2000 Data Cleaning 101 Ronald P. Cody 13
SESUG 2000 Dead Graphs - RIP (How Interactive Graphical EDA Techniques Can Markedly Enhance the Analysis/Display of Our Data) Dave DesJardins source 9
SESUG 2000 Underlying Construct Analysis (UCA): Where Individual Systems End and Human Systems Begin Alvin L. Killough source 8
NESUG 2000 Data Quality Control in Multi-State, Multi-year, Multi-type Databases: A Method for Examining Year-to-Year Percentage Changes Li wan Chen 8
SEUGI 2000 Benefits From Merging Datawarehouses [presentation] Jurgen Wielandts,
Sophie Ceyssens		 source 18
SEUGI 2000 Delfos: gas demand forecasting [presentation] Jose Manuel Galvez Canamaque source 45
SEUGI 2000 Finding the needle in a haystack: Fraud Detection on million records [presentation] Thierry Van de Merckt source 28
SEUGI 2000 Insurance Rate Making Using Data Mining [presentation] Bernd Drewes source 50
SEUGI 2000 Supply Chain Optimization and Planning [presentation] Patrick Xhonneux source 47
SEUGI 2000 Two sides to the modelling problem [presentation] Philip Whittall source 14
PharmaSUG 2000 A SAS Tool for the Presentation and Statistical Analysis of Data from Bioavailability and Bioequivalence Studies Melvin S. Munsaka,
Carl R. Haske		 8
PharmaSUG 2000 From Data to Study Report in One Step: A SAS Macro for the 2,2,2 Crossover Design Amy Morris,
Thomas E. Bradstreet		 5
PharmaSUG 2000 Visualize Your Regression Analysis Fan Xu 7
SUGI 2000 Dead Graphs - RIP (How Interactive Graphical EDA Techniques Markedly Enhance Data Analysis/Display) Dave L. DesJardins source 9
SUGI 2000 SAS Programs to Get the Most from X-12-ARIMA's Modeling and Seasonal Adjustment Diagnostics Catherine C. Hood source 6
SUGI 2000 Version 8 Base SAS Performance: How Does It Stack Up? Robert S. Ray source 7
SESUG 1999 Forecasting Army Officer Attrition with Logistic Regression Using The SAS System Douglas L. McAllaster source 10
WUSS 1999 Application of Poisson Model in Non-Market Valuation: Cave Rock Climbing Data Analysis Using SAS Macros Yuanfang Lin source 5
NESUG 1999 Data Cleaning 101 Ronald P. Cody 10
NESUG 1999 Exploratory Data Analysis: Getting to Know Your Data Michael A. Walega 8
NESUG 1999 PROC SQL for DATA Step Die-Hards Christianna S. Williams 10
SEUGI 1999 Data mining methodologies for business: fraud detection [presentation] Bernd Drewes source 22
SEUGI 1999 Outlier detection at EUROSTAT [presentation] Pacal Loosveldt source 31
SUGI 1999 A SAS Module/Macro Program for Computing Statistical Power Curves for Detecting Treatment Effect David Olaleye source 6
SUGI 1999 Robust Outlier Identification using SAS Jack N. Shoemaker source 8
SUGI 1999 The Science and Art of Market Segmentation Using PROC FASTCLUS Mark E. Thompson source 5
SUGI 1999 Two Macros to Compute the Median for a List of Variables Fan Xu source 4
SCSUG 1998 Implementing Robust Statistical Calculations for Minimizing the Effect of Outliers Rona Tracy 4
SCSUG 1998 JMP Reveals the Truth: Statistics Can Be Fun! William R. Gjertsen 10
SCSUG 1998 Laboratory Data Management and Reporting O. M. Little 30
NESUG 1998 Developing Ratio Edit Parameters with SAS for the Economic Census Richard W. Graham 10
NESUG 1998 JMP Reveals the Truth: Statistics Can Be Fun! William R. Gjertsen 12
NESUG 1998 Knowledge Discovery: The Seven New Multivariate Identification Model Tools Nicholas Skovran 5
NESUG 1998 Using SAS/IML to Calculate L-Moments for the Univariate Distribution Shape Parameters Skewness and Kurtosis Michael A. Walega 8
SESUG 1998 An Applicatio.n of Cluster Analysis in the Financial Services Industry Satrsh Nargundkar,
Strategic Decision		 6
SESUG 1998 Applications Development Eric C. Brinsfield 4
SESUG 1998 Developing Ratio Edit Parameters with SAS for the Economic Census Richard W. Graham 10
SESUG 1998 X-12-Graph: Visual Diagnostics for Time Series Modeling and Seasonal Adjustment Catherine C. Hood. U.S 6
PNWSUG 1998 The Science and Art of Market Segmentation Using PROC FASTCLUS Mark E. Thompson 6
SEUGI 1998 Bioequivalence standardized Julian Singer source 6
SUGI 1998 A Revolution in Data Analysis: How New, Very Powerful, Easy to Use, Graphical Data Analysis Tools and Techniques Can Empower Even Novice Subject Matter Specialists Dave L. DesJardins source 8
SUGI 1998 CHEKOU T : A SAS Program to Screen for Outliers James Handsfield source 3
SUGI 1998 DEMOXRPT: Macros for Writing Exception Reports; Perform Range and Logic Checks on a Data Set; Write File of Exceptions to Edit and Use for Updates Ronald J. Fehd source 4
SUGI 1998 Finding the Solution to Data Mining: A Map of the Features and Components of SAS Enterprise Miner Software Table of Contents John C. Brocklebank,
Mark Brown		 source 24
SUGI 1998 Programming and Other Features of the JMP Calculator Daniel J. Obermiller source 8
WUSS 1997 Diagnostic Plots in Regression Analysis George C. J. Fernandez source 8
WUSS 1997 Logistic Regression Modeling in Complex Surveys: Examples Using LOGITSE SAS Macro Jesse Albert Canchola,
Brian D. Marx,
Joseph A. Catania		 source 10
WUSS 1997 On Time and Under Budget: Guidelines for Success Using the SAS System with Traditional Structured Techniques Marc Daniels,
Clark Roberts		 source 4
NESUG 1997 A Self-Organizing Median-Estimation Model Susan B. Garavaglia 9
NESUG 1997 Application of SAS/ACCESS Software & DCL to Simplify Management and Analysis of Clinical Data For In Vitro Diagnostic Medical Devices Denise Cervelli 6
NESUG 1997 Attribute Smoothing: A Pattern Forecasting Technique David R. Roberts 4
MWSUG 1997 A simple macro to identify samples for reanalysis Robert H. Gallavan,
James M. McKim		 3
MWSUG 1997 Linear Regression Modeling using the SAS System: A Real-World Example Comparing the Factors Influencing Charity Care and Bad Debt in Wisconsin Hospitals Lynette A. Gerstner 7
SEUGI 1997 Data Mining and SAS/SPECTRAVIEW software: a case study Annie Postic,
Bengt Bengtsson		 source 36
SEUGI 1997 Data Mining with The SAS System Gerhard Held,
John C. Brocklebank		 source 42
SEUGI 1997 Social security benefits: using a warehouse to forecast and monitor social change Sandy Fitzpatrick,
Stephen Donnelly		 source 15
SEUGI 1997 SPC system in steel works and control of the implemented SPC Cinzia Amandonico,
Franca Vicino,
Stefano Conedera		 source 4
SUGI 1997 Characterization of Variance in Medical Diagnostics: The Analysis of "Usual" Data John A. Wass source 5
SUGI 1997 Detection of Model Specification, Outlier, and Multicollinearity in Multiple Linear Regression Models Using Partial Regression/Residual Plots George C. J. Fernandez source 6
SUGI 1997 Introduction to Building a Linear Regression Model Leslie A. Christensen source 7
SUGI 1997 Introduction to JMP under Windows: Hands-On Workshop Outline Jenny Aquino Kendall,
Al M. Best,
Charles E. Shipp		 source 6
SUGI 1997 JMP Reveals the Truth: Statistics Can Be Fun! William R. Gjertsen source 11
SUGI 1997 On Time and Under Budget: Guidelines for Success Using the SAS System with Traditional Structured Techniques Marc Daniels,
Clark Roberts		 source 4
SESUG 1996 Discriminant Analysis via Statistical Packages Carl J Huberty,
Laureen L. Lowman		 11
NESUG 1996 The Bisquare Weighted Analysis of Variance: A Technique for Nonnormal Distributions Rebecca Regeth,
William Stine		 9
WUSS 1996 Preliminary Data Mining for Subgroups in a Hospital Inpatient Population Anthony M. Dymond source 6
WUSS 1996 SAS Macros and Fraud Detection in the Department of Defense Wayne F. Woo,
Joyce Hamza		 source 5
WUSS 1996 Using Survey Data: Tips to Pick Up Speed on the Road to Analysis Cynthia L. Williamson,
Suzanne D. Kreutzer		 source 6
SEUGI 1996 Computer-aided sales forecasting (CAS-FO) and the art of planning - a paradox? Thomas Schmidt-Melchiors,
Wolfgang Schum		 source 12
SEUGI 1996 Diagnostics and estimation procedures of quantitative dose response relationships using SAS ... Hans-Peter Altenburg source 8
SEUGI 1996 Visualisation in data mining Annie Postic source 23
SUGI 1996 Improving the Quality of Survey Data through an Interactive Data Analysis System Robert Hood,
Mark Apodaca		 source 8
NESUG 1995 A Methodology For Supporting Summary Selectivity Dennis J. Clague 7
NESUG 1995 A SAS/AF FRAME Application for Clinical Laboratory Review Denis Michel 7
SESUG 1995 Information Visualization Data Driven Plots In Clinical Research... What Next? George A. Nestory 6
SEUGI 1995 APPS - a 5th Generation Sales Planning and Forecasting System Sven Viergutz source 12
SUGI 1995 An Introduction to JMP Software, Release 3.1, SAS Institute's Statistical Visualization Software for Both Macintosh and Windows William R. Gjertsen source 7
SUGI 1995 Functions to Facilitate Decision Making: A Flexible Approach for Screening Data Robert Chu,
Susan Tideman		 source 8
SUGI 1995 Interactive Analysis of Survey Data Using SAS/AF and SAS/EIS Software Robert Hood source 6
SUGI 1995 Interactive Visualization and Statistical Interpretation of Market Share, Competitive Price, Stock and Mortgage Loan Data Using JMP 3.1 James Daughtry,
Jonathan Pinder,
Edwin Tang,
William R. Gjertsen		 source 14
WUSS 1994 Visualization of Scientific Data: Specialty Graphs Without Using Annotate Arthur L. Carpenter source 9
NESUG 1994 Exploratory Data Analysi When You Don't Have SAS/INSIGHT Michael A. Walega 10
SEUGI 1994 Estimating Robust Scale Measures Using SAS Software Hans-Peter Altenburg source 7
SEUGI 1994 Graphical Extensions for Principal Component Analysis (Insight of a Dream PCA) Philippe Besse source 16
SEUGI 1994 Using SAS/IML Software to Develop Flexible Regression Models Edwin Gillespie,
Noel Wilson		 source 5
SUGI 1994 Constructing Multivariate Control Charts with SAS Software Melissa A. Durfee source 9
SUGI 1994 Exploring Data With Base SAS Software Thomas J. Winn Jr. source 6
SUGI 1994 Guided Data Analysis with SAS/LAB Software Katherine J. Roggenkamp source 10
SUGI 1994 Model Diagnostics for Three Factor Models Eric P. Smith,
Kyoungah See		 source 5
SUGI 1994 Recent Issues in Statistical Process Control: SAS Solutions USing Statistical Modeling Procedures Robert N. Rodriguez source 18
SUGI 1994 SAS Software Utilization in the Production of Fibers Robert V. Baxley Jr.,
Jerry L. Oglesby		 source 8
SUGI 1994 Visualization of Scientific Data: Specialty Graphs Without Using Annotate Arthur L. Carpenter source 9
NESUG 1993 Constructing Multivariate Control Charts is SAS Melissa A. Durfee 9
NESUG 1993 Use of PROC IML to Calculate L-Moments for the Univariate Distributional Shape Parameters Skewness and Kurtosis Michael A. Walega 8
WUSS 1993 Visualization of N-Dimensional Databases Using Parallel Coordinates J. J. Helly,
Arthur L. Carpenter		 source 4
SCSUG 1993 Exploring Data Using Base SAS Software Thomas J. Winn Jr. 30
MWSUG 1993 Generalized Least Squares Estimation in Heteroscedastic Linear Models George W. Pasdirtz 7
MWSUG 1993 Graphical Methods for the Interpretation of Linear Regression Models Simin Kavoossi,
Timothy E. Cooley		 7
SEUGI 1993 Data Visualisation with SAS/INSIGHT Software Gerhard Held source 10
SEUGI 1993 Exploratory Data Analysis Using SAS Software Gerhard Held source 11
SEUGI 1993 Extensions to Multivariate Descriptive Analysis Yves Roy source 14
SUGI 1993 A Fuzzy Clustering Approach in Support of Identifying Influential Observations and the Computation of Multiple Outlier Diagnostics Konstantinos Triantis,
Ritu Puri,
William L. Seaver		 source 6
SUGI 1993 A Simulation-Based Project For Experimental Design Based on SAS Software Michael Friendly source 8
SUGI 1993 Exploratory Data Analysis Using SAS Software Greg J. Weier,
Randall D. Tobias		 source 11
SUGI 1993 Guided Data Analysis with SAS/LAB Software Katherine J. Roggenkamp,
Wayne E. Watson,
Randall D. Tobias		 source 7
SUGI 1993 Practical Econometric Analysis for Assessment of Real Property Using the SAS System on Personal Computers Shah Amal,
Robert Weselowski		 source 6
SUGI 1993 SAS/LAB Software for Guided Data Analysis Wayne E. Watson,
Katherine J. Roggenkamp,
Randall D. Tobias		 source 7
SUGI 1993 The Laboratory Review System: A SAS-based Graphical and Statistical Tool Developed for a Computer-Assisted New Drug Application (CANDA) Submission Russell R. Holmes,
David A. Bright		 source 6
SUGI 1993 Using SAS/GRAPH Software to Create Unclassed Choropleth Maps Michael Swift,
Diane Nishri		 source 6
SESUG 1993 Outliers and Redundant Variables in Principal Component and Factor Analysis G. Mora-Aguilera,
R. Kiltiei,
D. Nleto-Angel,
D. Teliz		 10
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
NESUG 1992 Data/Variables Reduction by Principal Componets, Battery Reduction and Variable Clustering Joseph Massoro,
Zhini Zhang		 11
NESUG 1992 Getting to Know Your Data Using SAS Felicia Borglum 7
NESUG 1992 The Laboratory Review Systems: A SAS-based Graphical and Statistical Tool Developed for a CANDA Submission Russell R. Holmes,
David A. Bright		 6
NESUG 1992 The Statistical Provider Utilixation Review System (SPURS): A SAS Based System for Health Care Provider Profiling Drew Thraen,
Lawrence Kane,
Peter An		 5
MWSUG 1992 Using SAS Macro Facilities to Simplify A Large Multi-Event Statistical Analysis Douglas P. DeYoung 6
SEUGI 1992 Guided Data Analysis with SAS/LAB Software Gerhard Held source 7
SUGI 1992 Checking Out-of-Range Data Aileen L. Yam source 4
SUGI 1992 Evaluating Export Marketing Decisions Using Cluster Analysis and Correspondence Analysis Marcus Schmidt,
Jesper Strandskov,
Gerald Albaum		 source 5
SUGI 1992 Interactive Data Analysis Strategies Alvin M. Best III source 6
SUGI 1992 Ordination and Display of Multivariate Data E. Barry Moser source 10
SUGI 1992 SAS Classes for Nonprogrammers in the Clinical Data Management World Susan V. Hale source 4
SEUGI 1991 An Example of the Use of Historical Information in the Analysis of Pharmaceutical Screening Trials Egbert Biesheuvel,
R. A. J. Wixley		 source 9
SUGI 1991 A SAS Procedure for Outlier Detection in Bioavailability/ Bioequivalence Studies Jyh-Shiun Lin,
Shein-Chung Chow,
Siu-Keung Tse		 source 5
SUGI 1991 Analysis of 2 x 2 Cross-over Trials Using an Integrated Macro Package Harvie Chang,
Tamara R. Strang		 source 6
SUGI 1991 Box and Whiskers Revisited - Using SAS/GRAPH Software to Produce Box and Whiskers Plots Hedy Weissinger source 4
SUGI 1991 Robust Estimator for Linear Regression Ashok Mehta source 7
SUGI 1991 Statistical Graphics for Multivariate Data Michael Friendly source 6
SUGI 1991 Testing for Cluster Structure before a Cluster Analysis Brian McArdle source 5
NESUG 1990 Regression Analysis In The Real World Edith Flaster 7
SEUGI 1990 Multivariate Outlier Detection Christian Derquenne source 9
SEUGI 1990 Robust Estimation of Radio Immuno Assays Using SAS Software Hans-Peter Altenburg source 8
SUGI 1990 Segmenting the Tourist Market Using Factor Analysis and Cluster Analysis Marcus Schmidt,
Hans Merser		 source 6
SUGI 1990 The SAS System for Statistical Graphics - A Preview Michael Friendly source 6
SUGI 1990 Using the Interactive Features of the REG Procedure Rudolf J. Freund source 8
SUGI 1990 Using the SAS System to Prepare Hospital Inpatient Claims Data for Case-Mix Analyses Daniel R. Bretheim source 8
SUGI 1989 A Class of Highly Efficient Resistant and Robust Estimators for Simple Linear Regression for Use with the SAS System Evelyn A. Adler source 6
SUGI 1989 Computing the Standard Deviation from a Geometric Mean Daniel R. Bretheim source 3
SUGI 1989 Modeling Policy Impact Daniel R. Bretheim source 5
SUGI 1989 Most Creative Use of the Software-Monochrome Leslie Worf source 116
SUGI 1989 Performance Function for Aircraft Production Using the SYSNLIN Procedure and L2 Norm Estimation Kimberly J. LeBouton source 3
SUGI 1988 Graphical Presentation of Clinical Data Using SAS Macros Pan-Yu Lai,
Thomas E. Schneider		 source 4
SUGI 1988 The Analysis of Complete Blocks Using Methods Based on Ranks Ronald L. Iman source 9
SUGI 1988 Transferring a Mainframe Data-checking Application to the SAS System for Personal Computers: The Agony and the Ecstasy Dorothea Collins,
Joan Derrico		 source 3
SUGI 1988 Using SAS/STAT Software's REG Procedure to Develop Sales Tax Audit Selection Models Kirk L. Johnson,
Richard W. Kulp		 source 6
SEUGI 1987 Tutorial on PROC REG Gerhard Held source 39
SUGI 1987 Confidence Limits for the Product Moment Correlation Coefficient Based upon Normalizing Transformations Herbert Hamilton source 6
SUGI 1987 Estimation of Variance Components in Mixed Factorial Models Including Model-based Diagnostics Ronald H. Bremer,
John W. Green,
Ronald R. Hocking		 source 6
SUGI 1987 Measures of Multivariate Skewness and Kurtosis Ronald Kalinoski,
NamJun Kang		 source 6
SUGI 1987 Using SAS/GRAPH Software to Display Box-Whisker Plots Charles B. Scott source 6
SUGI 1986 A Generalized Growth Curve Procedure for the Analysis of Incomplete Longitudinal Data Kenneth O. Story,
Edward F. Vonesh		 source 6
SUGI 1986 Using SAS Software in the Design and Analysis of Two-Level Fractional Factorial Experiments Joanne R. Wendelberger source 6
SUGI 1986 Variable Selection and Case Analysis in Regression Gerald R. Hobbs source 6
SUGI 1985 Bounded Influence Regression Using SAS Software David Giltinan source 6
SUGI 1985 Box Plots and More Box Plots - A Generalized SAS Macro Donna L. Stock source 6
SUGI 1985 Cumulative Sum (CUSUM) Control Schemes J.M. Lucas source 6
SUGI 1985 Multivariate Data Analysis Using the SAS System E. James Harner source 6
SUGI 1985 PROC ELPRINT: a Print Procedure that Supports Footnotes and Outlier Detection George F. Fraction,
Jeffrey B. Shotts,
Richard E. Skrzynecki,
S. Stanley Young		 source 6
SUGI 1985 PROVAL-An Automated Method for Evaluating Trade and Consumer Promotions for Package Goods Industries Ambar G. Rao,
Ross Dennis,
Douglas Grady		 source 5
SUGI 1985 STARS and FACES - Procedures for Constructing Graphical Profiles of Multivariate Data Harold W. Gugel source 6
SUGI 1984 Workload Characterization Using PROC FASTCL US H. Pat Artis source 8
SUGI 1983 Robust Discriminant Analysis Anthony A. Billings,
E. James Harner		 source 6
SUGI 1983 Robust Regression and PROC JACKREGR Daniel M. Chilko,
Gerald R. Hobbs		 source
SUGI 1982 Basic Time Series Tools for Business Forecasting Mary Sue Dickerson,
Franklin S. Young		 source 6
SUGI 1982 Four Topics in Statistics Rudolf J. Freund source 8
SUGI 1982 Multidimensional Scaling by Least Squares Cynthia H. Null,
Warren S. Sarle		 source 8
SUGI 1982 Statistical Review of Inpatient Services: A Systematic Approach Jennifer Anderson,
Gregory Lenhart,
Janice L. Weener		 source 2
SUGI 1982 Weibull Regression and Hazard Estimation Jan M. Hanley,
William H. Rogers		 source 11
SUGI 1981 On the Role of Redundant Information in Error Detection Ronald W. Helms source 5
SUGI 1981 Robust Measures of Scale in Outlier Detection Paul W. Fingerman source 6
SUGI 1981 Robust Modeling of Data Using PROC MATRIX Anthony A. Billings,
E. James Harner,
Ronald D.King		 source
SUGI 1981 SAS Outlier Macros: A Banking Problem James A. Calloway,
William L. Seaver		 source 5
SUGI 1980 Pre-programmed Routines for an Applied Linear Models Course James A. Calloway,
William L. Seaver		 source 6
SUGI 1979 A SAS Macro for Robust Multiple Regression Charles McElrea source 4
SUGI 1979 Estimating Passenger Demands from Truncated Samples Franklin S. Young source 5
SUGI 1977 PROCEDURE WILCOX - A SAS-76 Procedure for Estimating the Ratio of Two Random Variables K. Deva Kumar,
Rodney H. Strand		 source 6
SUGI 1977 Some Graphical and Statistical Descriptions of Interactions Paul N. Hinz source 5
SUGI.ONE 1976 Econometric Uses of SAS Max Moszer,
Martha S. Shuler		 source 26
SUGI.ONE 1976 Two Tools for Residual Analysis in Multiple Regression Ronald B. Wiley source 36

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