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426 papers and 7 presentations; 382 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
PharmaSUG 2026 Evaluation of Azure OpenAI ChatGPT API as Code Assistance Tools for Statistical Programming in SAS, R and Python. Ajay Gupta,
Misikir Tesfaye		 source 25
PharmaSUG 2026 Regression Analysis Made Easy Using R Zheyuan Yu,
Kirk Paul Lafler,
Zichun Gao,
Jiaxin Xu,
Zeqi Li,
Ruochen Shao		 source 32
PharmaSUG 2026 Streamlining Workflows in Real-World Evidence Studies with an R-Based Automation Tool Lihai Song source 16
PHUSE APAC 2026 Leveraging Large Language Models (LLMs) for Missing Data Imputation and Interpretation of Real-World Evidence Outputs Spencer Langerman,
Rahul Manohar Somavanshi		 source
presentation source		 12
PHUSE EU 2025 GLMM and GEE for Categorical Repeated Measures - Linking SAS and R Miriam Amor source
presentation source		 16
MWSUG 2025 Code Smarter, Not Harder: The 5 C's of ChatGPT for the SASsy Professional Kirk Paul Lafler,
Charu Shankar		 source 49
MWSUG 2025 Conducting Survival Analysis in SAS using Medicare Claims as a Real-world data source Jayanth Iyengar source 32
SESUG 2025 Going from Zero to Report Ready with PROC TABULATE Rachel Straney 13
SESUG 2025 Introduction to Data Simulation Jason Brinkley 10
SESUG 2025 Modernizing Predictive Modeling in SAS: When to Move Beyond PROC GLM Duha Khan,
Sriya Venkat,
Sydney McDermott		 8
WUSS 2025 Automating Clinical Study Reports: A Modular Framework for Continuous Data Reporting William Wei source 7
WUSS 2025 Conducting Survival Analysis in SAS using Medicare Claims as a Real-world data source Jayanth Iyengar source 32
PharmaSUG 2025 Code Smarter, Not Harder: The 5 C's of ChatGPT for the SASsy Professional Charu Shankar,
Kirk Paul Lafler		 source 49
PharmaSUG 2025 Conducting Survival Analysis in SAS using Medicare Claims as a Real-world data source Jayanth Iyengar source 32
PharmaSUG 2025 Leveraging Python for Statistical Analysis in Public Health: Techniques and Visualizations for Life Sciences Professionals Michael Carnival source 14
PharmaSUG 2025 Methodology for AI-driven Outcome Prediction for Patients with Atrial Fibrillation After Transcatheter Aortic Valve Implantation (TAVI) Felix Just,
Krishna Padmanabhan,
Parth Jinger,
Amanda Borrow,
Rüdiger Smolnik,
Eva-Maria Fronk,
Neelam Yadav,
Sergei Krivtcov,
Stas Zakharkin,
Martin Unverdorben,
Asmir Vodencarevic		 source 6
MWSUG 2024 A General Review of Fuzzy Matching Techniques and Their Capabilities Using SAS Kirk Paul Lafler source 31
PHUSE EU 2024 A programmer's introduction to modelling with proc mixed, focusing on how to debug and validate, common mistakes and how to interpret the output George Gibson source
presentation source		 6
PHUSE EU 2024 Automating Real-World Data Analysis Using R Packages and Shiny: A Three-Stage Workflow Stavros Oikonomou,
Louise Raiteri		 source
presentation source		 8
SESUG 2024 A Comprehensive Analysis of the Relationship Between Depression, Sleep Deprivation, and Self-Esteem Using Advanced Statistical Methods Muslihat Adejoke Gaffari source 43
SESUG 2024 Comparative Tools in SAS: Analyzing Self-Reported versus Imputed Values Neesha Nathwani,
Sarah Woodruff		 source 30
SESUG 2024 Introduction to Clustering Algorithms Jason Brinkley source 10
WUSS 2024 From Keys to Credit: A Deep Dive into Homeownership's Influence on Loan Quality Yi-Che Chen,
Debanik Chakraborty		 source 15
WUSS 2024 Interactive Data Analysis and Exploration with composR: See the Forest AND the Trees Steve Wade,
Sudhir Kedare		 source 6
PharmaSUG 2024 A Simple Way to Make Adaptive Pages in Listings and Tables Yi Guo source 9
PharmaSUG 2024 Interactive Data Analysis and Exploration with composR: See the Forest AND the Trees Steve Wade,
Sudhir Kedare,
Matthew Travell,
Chen Yang,
Jagan Mohan Achi		 source 7
PharmaSUG 2024 Pictorial Representation of Adverse Events (AE) Summary - A new perspective to look at the AE data in Clinical Trials Pradeep Acharya,
Anurag Srivastav		 source 11
PharmaSUG 2024 Semi-Automated and Modularized Approach to Generate Tables for Clinical Study - Categorical Data Report William Wei,
Shunbing Zhao		 source 8
PharmaSUG 2024 Shift gears with "gt": Finely tuned clinical reporting in R using "gt" and "gt summary" packages Rajprakash Chennamaneni,
Sudhir Kedare,
Jagan Mohan Achi		 source 6
PHUSE US 2024 Harnessing AI for Health Equity and Inclusivity in Risk-Based Monitoring Finn Janson source
presentation source		 12
WUSS 2023 Getting Started with the SGPLOT Procedure Joshua M. Horstman source 18
WUSS 2023 Introduction to Machine Learning - Descriptions and Best Practices Jim Box source 13
WUSS 2023 Open-Source Essentials HOW - R and RStudio Wendy Christensen source 17
SESUG 2023 Visualizing Chronic Lung Disease Incidence in SAS; An Educational Journey to Data Visualization Natalie A. Jordan,
A. Nicole Ferguson,
Jessica G. Woo,
Kevin Gittner,
Reese H. Clark		 source 10
PharmaSUG 2023 Smart Use of SAS Output System and SAS Macro for Statistic Test Selection Mengxi Wang source 10
PharmaSUG 2023 What is Machine Learning, anyway? Jim Box source 11
SESUG 2022 Using SAS Macro and ODS Output to efficiently examine the descriptive and analytic statistics in epidemiology studies Yue Pan source 7
WUSS 2022 Attribute Reduction for Continuous Dependent Variables in SAS Alec Zhixiao Lin source 20
PharmaSUG 2022 Self Modifying Macro to Automatically Repeat a SAS Macro Function Chary Akmyradov source 6
PHUSE EU 2021 A Beginner's Guide to Data Analysis Shuva Dey source
video		 15
PHUSE EU 2021 Increasing Utility of Anonymised Data - Improved Banding Techniques [presentation] Jasper Enderman source
video		 14
PHUSE EU 2021 Programming Infrastructure to Automate Process Flow for CSS [presentation] Archana Nayak,
Salvatore Saporito		 source
video		 22
SESUG 2021 Back to Basics: Running an Analysis from Data to Refinement in SAS Deanna Naomi Schreiber-Gregory source 21
SESUG 2021 Coarsening Continuous Variables: An Automated Method to Create Categorical Version of Continuous Variables While Mitigating Loss of Precision Zach Acuff source 10
SESUG 2021 Moving beyond Frequency and Percentage to Chi Square, t-Tests, and Correlation Analysis Kelly D. Smith source 12
PHUSE US 2021 Demographic and Socio-economic Disparities in Preference to Getting Vaccinated by the Flu Shot versus the Flu Spray in the United States Swapna Ambati source
video
presentation source		 12
PharmaSUG 2021 Back to Basics: Running an Analysis from Data to Refinement in SAS Deanna Naomi Schreiber-Gregory source 21
SGF 2021 Back to Basics: Running an Analysis from Data to Refinement in SAS Deanna Naomi Schreiber-Gregory source
presentation		 20
SGF 2021 Haste Makes Waste: Don't Ruin Your Reputation With Hasty Regression Steven C. Myers source
presentation
sas		 39
SGF 2021 Investing in Education Intelligently Sam Edison,
Rushya Puttam,
Akhil Emani,
Nithisha Katta		 source
presentation		 7
SGF 2020 An Efficient Way to Create Descriptive Tables with Pairwise Comparison Ang Gao,
Chul W. Ahn		 source 10
SGF 2020 Analyzing Non-normal Data: Application to Missing Data Problems Niloofar Ramezani source 10
SGF 2020 Automation in SAS Visual Data Mining and Machine Learning Wendy Czika source 26
SGF 2020 Explanatory Machine Learning Model Plots for Epidemiological and Real-World Evidence Studies David Olaleye source 22
SGF 2020 Moving from Messy Data to a Clean Analytic Dataset: Common Data Management Techniques using SAS Bethany A. Bell source 27
SGF 2020 Obtaining National Readmission Estimates: Examining Readmission Rates in the United States Patrick Karabon source 9
SGF 2020 Survey Data Analysis Made Easy wth SAS Melanie Dove,
Katherine Heck		 source 8
SGF 2020 Using Python with Model Studio for SAS Visual Data Mining and Machine Learning Jagruti Kanjia source 35
SGF 2020 Visualizing America: SAS Graphical Depictions utilizing the American Community Survey (ACS 2018) [presentation] Wendy B. Dickinson source 12
SESUG 2019 A user-friendly and robust macro that produces a publication-ready Table 1 Daniel Brinton,
Marshall Chew		 source 5
SESUG 2019 Advanced Statistical Modeling within Machine Learning and Big Data Analytics Niloofar Ramezani,
George Mason		 source 16
SESUG 2019 Data-driven Programming Techniques using SAS Macros to Semi-automate Generation of Descriptive Tables in Healthcare Research Katie Mercaldi source 37
SESUG 2019 Doing More with the SGPLOT Procedure Joshua M. Horstman source 18
SESUG 2019 Medians/quartiles are shown for continuous data and counts/percentages are shown for categorical data Martha Wetzel source 5
SESUG 2019 Smoothing 3D mortality rates due to drug overdose and displaying death patterns with SAS/JMP software Nancy Han,
Rong Wei		 source 10
MWSUG 2019 Doing More with the SGPLOT Procedure Joshua M. Horstman 18
WUSS 2019 Choosing Wisely: Using the Appropriate Statistical Test for Trend in SAS Christina Park,
Jui-Ting Hsiung,
Melissa Soohoo,
Elani Streja		 source 10
WUSS 2019 Doing More with the SGPLOT Procedure Joshua M. Horstman source 18
WUSS 2019 Multi-Way (more than two) Splits In Decision Trees Russell M. Lavery source 8
PharmaSUG 2019 Create publication-ready variable summary table using SAS macro Geliang Gan source 12
PharmaSUG 2019 One Macro to Produce Descriptive Statistic Summary Tables with P-Values Rajaram Venkatesan,
Harinarayanan Gopichandran		 source 14
PharmaSUG 2019 SAS V9.4 MNAR statement for multiple imputations for missing not at random in longitudinal clinical trials Lingling Li source 11
PharmaSUG 2019 The Power of Data Visualization in R Oleksandr Babych source 21
SGF 2019 Analyzing Structural Causal Models using the CALIS Procedure Banoo Madhanagopal,
John Amrhein		 source 23
SGF 2019 Asking the Right Questions: A study in Multiclass Imbalanced Classification for H1-B Visas Matthew Bunker,
Owen Kelly		 source 7
SGF 2019 Causal Analyses Using Structural Equation Models Banoo Madhanagopal,
John Amrhein		 source 23
SGF 2019 Don't Let Complex Survey Data Get the Best of You! SAS Survey PROCs for Categorical Data Analysis Charlotte Baker source 16
SGF 2019 Getting Started with the SGPLOT Procedure Joshua M. Horstman source 19
SGF 2019 Latin Hypersquare Sampling and Genetic Algorithm in SAS/IML for Hyperparameter Optimization Andrea Magatti source 16
SGF 2019 Monitoring the Relevance of Predictors for a Model Over Time Ming-Long Lam source 16
SGF 2019 The Benefits of Keeping It Casual: Investigating Stress-Mediated Health Outcomes with PROC CAUSALMED Daniel Muzyka,
Matthew Lypka		 source 19
PHUSE US 2019 Check Your Data: Tools for Automating Data Assessment Paul Stutzman source
presentation source		 10
PHUSE EU 2018 Collinearity in Mixed Models John Hendrickx source
presentation source		 11
SESUG 2018 Automated Comparison Tables using PROC REPORT Evan Kwiatkowski source 6
SESUG 2018 Doing More with the SGPLOT Procedure Joshua M. Horstman source 18
SESUG 2018 Fuzzy Matching Programming Techniques Using SAS Software Stephen B. Sloan source 29
SESUG 2018 Getting Started with the SGPLOT Procedure Joshua M. Horstman source 18
SESUG 2018 Going from Zero to Report Ready with PROC TABULATE Rachel Straney source 13
SESUG 2018 Introduction to Data Simulation Jason Brinkley source 9
SESUG 2018 Table Taming - Using ODS to Simplify Data Presentation Emily Perry source 12
MWSUG 2018 Getting Started with the SGPLOT Procedure Joshua M. Horstman 18
WUSS 2018 Getting Started with the SGPLOT Procedure Joshua M. Horstman source 18
WUSS 2018 Validating User-Submitted Data Files with Base SAS Michael A. Raithel source 16
PharmaSUG 2018 R 101: The base Package Arthur X. Li source 22
PharmaSUG 2018 Using ODS LAYOUT, GTL, and ODSTEXT to Generate a Compact Graphical Codebook Shane Rosanbalm source 4
PharmaSUG 2018 Using SAS GTL to Visualize Data When there is Too Much of It to Visualize Nathaniel Derby,
Perry Watts		 source 22
SGF 2018 A Study of Modeling Approaches for Predicting Dropout in a Business College Helmut Schneider,
Xuan Wang		 source 8
SGF 2018 Claim Risk Scoring Using Survival Analysis Framework and Machine Learning with Random Forest Yuriy Chechulin source 15
SGF 2018 Fuzzy Matching Programming Techniques Using SAS Software Stephen B. Sloan,
Kirk Paul Lafler		 source 24
SGF 2018 New Ways to Incorporate Continuous Predictors in Generalized Linear Models Anthony Salis,
Angela Wu,
Gordon Johnston		 source 15
SGF 2018 Retail Product Bundling: A New Approach Bruno Nogueira source 18
SGF 2018 Validating User-Submitted Data Files with Base SAS Michael A. Raithel source 16
SESUG 2017 Fuzzy Matching Programming Techniques Using SAS Software Stephen B. Sloan,
Kirk Paul Lafler		 source 25
SESUG 2017 PMML & SAS: An Introduction to PMML and PROC PSCORE Andrew Gannon source 9
SESUG 2017 Using Categorical Variables in Regression Analysis Jonas V. Bilenas source 15
SCSUG 2017 Fuzzy Matching Programming Techniques Using SAS Software Kirk Paul Lafler,
Stephen B. Sloan		 source 25
PHUSE EU 2017 How to Fit Longitudinal Data with Proc MCMC Maud Henion source
presentation source		 16
MWSUG 2017 Intermediate SAS ODS Graphics Chuck Kincaid 28
MWSUG 2017 Multiple Imputation of Family Income Data in the 2015 Behavioral Risk Factor Surveillance System Jia Li,
Aaron Sussell		 4
WUSS 2017 A Method for Simultaneously Programming Mock and Computed Tables Michael Williams source 8
WUSS 2017 A Quick Look at Fuzzy Matching Programming Techniques Using SAS Software Kirk Paul Lafler,
Stephen B. Sloan		 source 25
WUSS 2017 Analysis of Complex Survey Data with SAS Christine Wells source 6
WUSS 2017 Standardized Approaches for Analyzing Quality Improvement Interventions in Healthcare Settings Polina Kukhareva source 20
PharmaSUG 2017 Check Your Data: Tools for Automating Data Assessment Paul Stutzman source 12
PharmaSUG 2017 Survival 101 - Just Learning to Survive Leanne Goldstein,
Rebecca Ottesen		 source 20
SGF 2017 A Moment-Matching Approach for Generating Synthetic Data in SAS Brittany Bogle,
Jared Erickson		 source 17
SGF 2017 A SAS Macro for Covariate Specification in Linear, Logistic, and Survival Regression Sai Liu source
zip		 19
SGF 2017 Analyzing the Effectiveness of COPD Drugs Through Statistical Tests and Sentiment Analysis Indra Kiran Chowdavarapu,
Dursun Delen,
Vivek Manikandan Damodaran		 source 23
SGF 2017 Exploration of Information Technology-Related Barriers Affecting Rural Primary Care Clinics Ipe Simon Paramel,
Ankita Srivastava,
Onkar Jadhav,
Jennifer Briggs,
Georgina Ankrah		 source 11
SGF 2017 Fitting Complex Statistical Models with NLMIXED and MCMC Procedures Robin High source 14
SGF 2017 Getting Classy: A SAS Macro for CLASS Statement Automation Erica Goodrich,
Daniel Sturgeon,
Kathryn Schurr		 source
pdf		 12
SGF 2017 Intermediate SAS ODS Graphics Chuck Kincaid source
zip		 28
SGF 2017 The ODS EXCEL statement: Tips and Tricks for the TABULATE and REPORT Procedures Richard A. DeVenezia source 17
SGF 2017 The Three Amigos Factors: Determining Term Deposit Purchases: How a Bank Can Get Other People's Money Gina Colaianni,
Bogdan Gadidov,
Matthew Mitchell		 source 59
SGF 2017 The Truth Is Out There: Leveraging Census Data Using PROC SURVEYLOGISTIC Richard Dirmyer source 5
SCSUG 2016 Determining the functionality of Water Pumps in Tanzania Using SAS EM and VA Indra Kiran Chowdavarapu,
Vivek Damodaran Manikandan		 source 9
SCSUG 2016 Show Me the Money! Text Analytics for Decision-Making in Government Spending Tom Sabo source 13
SESUG 2016 A Short Introduction to Longitudinal and Repeated Measures Data Analyses Leanne Goldstein source 19
SESUG 2016 Factors of Multiple Fatalities in Car Crashes Bill Bentley,
Gina Colaianni,
Kennedy Onzere,
Cheryl Joneckis,
Xuelei (Sherry) Ni		 source 62
SESUG 2016 Introduction to Data Simulation Jason Brinkley source 8
PHUSE EU 2016 Considerations in the Use of Propensity Scoresin Observational Studies Lawrence Rasouliyan,
Estel Plana		 source
presentation source		 17
PHUSE EU 2016 The TFL Workbench: Tools to Standardise and Accelerate Table, Figure and Listing (TFL) Programming Iain Humphreys,
Hansjörg Frenzel		 source
presentation source		 10
MWSUG 2016 Automating the Process of Generating Publication Quality Regression Tables through SAS Base Programming Ji Qi 16
MWSUG 2016 Fitting Complex Statistical Models with PROCs NLMIXED and MCMC Robin High 16
MWSUG 2016 Fitting Your Favorite Mixed Models with PROC MCMC Fang K. Chen,
Gordon Brown,
Maura E. Stokes		 27
WUSS 2016 A SAS macro for quick descriptive statistics Jenna Carlson source 4
WUSS 2016 Creating meaningful factors from dietary questionnaires Jenna Carlson source 9
WUSS 2016 Fitting Your Favorite Mixed Models with PROC MCMC Fang K. Chen source 27
WUSS 2016 Introduction to Survival Analysis in SAS Leanne Goldstein,
Rebecca Ottesen		 source 19
PharmaSUG 2016 Best Practices: Subset Without Getting Upset Mary F. O. Rosenbloom,
Kirk Paul Lafler		 source 17
PharmaSUG 2016 Handling Interim and Incomplete Data in a Clinical Trials Setting Paul Stutzman source 13
PharmaSUG 2016 What makes a "Statistical Programmer" different from a "Programmer" Arun Raj Vidhyadharan,
Sunil Mohan Jairath		 source 12
PharmaSUG 2016 What-s the Case? Applying Different Methods of Conducting Retrospective Case/Control Experiments in Pharmacy Analytics Aran Canes source 8
SGF 2016 A Short Introduction to Longitudinal and Repeated Measures Data Analyses Leanne Goldstein source 19
SGF 2016 Applying Frequentist and Bayesian Logistic Regression to MOOC data in SAS: a Case Study Yan Zhang,
Ryan Baker,
Yoav Bergner		 source
presentation		 7
SGF 2016 Correcting the Quasi-complete Separation Issue in Logistic Regression Models Xinghe Lu source 10
SGF 2016 Factors of Multiple Fatalities in Car Crashes Bill Bentley,
Gina Colaianni,
Cheryl Joneckis,
Sherry Ni,
Kennedy Onzere		 source 60
SGF 2016 Fitting Your Favorite Mixed Models with PROC MCMC Gordon Brown,
Fang K. Chen,
Maura E. Stokes		 source 27
SGF 2016 Improving Performance of Memory-Based Reasoning Model by Using Weight of Evidence Coded Categorical Variables Vinoth Kumar Raja,
Goutam Chakraborty,
Vignesh Dhanabal		 source 6
SGF 2016 Intermediate ODS Graphics Chuck Kincaid source 28
SGF 2016 Reducing and Screening Redundant Variables in Logistic Regression Models Using SAS/STAT Software and SAS Enterprise Miner Xinghe Lu source 10
SGF 2016 You Can Bet on It: Missing Observations Are Preserved with the PRELOADFMT and COMPLETETYPES Options Christopher J. Boniface,
Janet Wysocki		 source 7
MWSUG 2015 Intermediate SAS ODS Graphics Chuck Kincaid 28
SESUG 2015 Intermediate SAS ODS Graphics Chuck Kincaid,
Experis Business		 source 28
WUSS 2015 A Short Introduction to Longitudinal and Repeated Measures Data Analyses Leanne Goldstein source 19
WUSS 2015 Chi-Square and T-Tests Using SAS: Performance and Interpretation Jennifer L. Waller,
Maribeth H. Johnson		 source 12
WUSS 2015 ODS Output Data Sets That Work for You Stuart D. Long,
Edward Heaton,
Daniel R. Scharf		 source 29
WUSS 2015 Yes, PROC FREQ does that! AnnMaria De Mars source 15
PharmaSUG 2015 Statistical Analyses Across Overlapping Time Intervals Based on Person-Years John Reilly,
John R. Gerlach		 source 10
SGF 2015 Best Practices: Subset Without Getting Upset Mary F. O. Rosenbloom,
Kirk Paul Lafler		 source 17
SGF 2015 Chi-Square and T-Tests Using SAS: Performance and Interpretation Jennifer L. Waller,
Maribeth H. Johnson		 source 12
SGF 2015 Data Sampling Improvement by Developing the SMOTE Technique in SAS Lina Maria Guzman Cartagena source 9
SGF 2015 Don't Copy and Paste--Use BY Statement Processing with ODS to Make Your Summary Tables Jeffrey M. Gossett,
Mallikarjuna Rettiganti		 source 18
SGF 2015 Entropy-Based Measures of Weight of Evidence and Information Value for Variable Reduction and Segmentation for Continuous Dependent Variables Alec Zhixiao Lin source 27
SGF 2015 Forest Plotting Analysis Macro %FORESTPLOT Jeffrey P. Meyers,
Qian Shi		 source 18
SGF 2015 Getting Your Hands on Reproducible Graphs Rebecca Ottesen,
Leanne Goldstein		 source 19
SGF 2015 Multiple Imputation Using the Fully Conditional Specification Method: A Comparison of SAS, Stata, IVEware, and R Patricia A. Berglund source 17
SGF 2015 Predicting Readmission of Diabetic Patients Using the High-Performance Support Vector Machine Algorithm of SAS Enterprise Miner 13.1 Hephzibah Munnangi,
Goutam Chakraborty		 source 10
SGF 2015 Show Me the Money! Text Analytics for Decision-Making in Government Spending Tom Sabo source 13
SGF 2015 Statistical Analysis of Publicly Released Survey Data with SAS/STAT Software SURVEY Procedures Donna Brogan source 20
SGF 2015 Sums of Squares: The Basics and a Surprise Sheila Barron,
Michelle Mengeling		 source 8
SGF 2015 Using PROC SURVEYREG and PROC SURVEYLOGISTIC to Assess Potential Bias Lucy D'Agostino McGowan,
Alice Toll		 source 8
SESUG 2014 A Strip Plot Gets Jittered into a Beeswarm Shane Rosanbalm source 12
SESUG 2014 Don't be binary! Tales of Non-binary Categorical Regression Charlotte Baker source 6
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
PHUSE EU 2014 An Introduction to SAS Visual Analytics for the Health Care Sector Rhian Pilling source 19
MWSUG 2014 Creating an Easy to Use, Dynamic, Flexible Summary Table Macro with P-Values in SAS for Research Studies Amy Gravely,
Barbara Clothier,
Sean Nugent		 10
WUSS 2014 A SAS Macro to Produce Summary Statistics Tables Allowing Additional Stratification Amanda Liu,
David E. Tappe		 source 5
WUSS 2014 A Statistical and Visual Exploration of the Surveillance, Epidemiology, and End Results (SEER) Database Using SAS Christopher Yim source 10
WUSS 2014 Best Practices: Subset Without Getting Upset Mary F. O. Rosenbloom,
Kirk Paul Lafler		 source 17
WUSS 2014 Decision Trees as a Predictive Modeling Method Gerry Hobbs source 8
WUSS 2014 Getting Your Hands on Reproducible Graphics Rebecca Ottesen,
Leanne Goldstein		 source 17
PharmaSUG 2014 Methodology for Non-Randomized Clinical Trials: Propensity Score Analysis Dan Conroy source 5
PharmaSUG 2014 Survival 101 - Just Learning to Survive Leanne Goldstein,
Rebecca Ottesen		 source 19
PharmaSUG 2014 The Association of Morbid Obesity with Mortality and Coronary Revascularization among Patients with Acute Myocardial Infarction Ashwini S Erande,
Shaista Malik		 source 11
SGF 2014 Analyzing Data from Experiments in Which the Treatment Groups Have Different Hierarchical Structures Sharon Lohr,
Peter Schochet		 source 12
SGF 2014 CMS Core Measures, the Affordable Care Act, and SAS Visual Analytics Joe Whitehurst,
Diane Hatcher		 source 16
SGF 2014 Data Coarsening and Data Swapping Algorithms Tom Krenzke,
Katie A. Hubbell,
Mamadou Diallo,
Amita Gopinath,
Sixia Chen		 source 19
SGF 2014 Generating Dynamic Tables Using PROC SQL and PROC TABULATE Lovedeep Gondara source 8
SGF 2014 Graphs Useful for Variable Selection in Predictive Modeling Bob Moore source 9
SGF 2014 The Role of Customer Response Models in Customer Solicitation Center's Direct Marketing Campaign Arun Mandapaka,
Amit Kushwah,
Goutam Chakraborty		 source 12
WUSS 2013 A Quick and Dirty Descriptive Data Summary Nora Ruel,
Rebecca Nelson		 source 12
WUSS 2013 A Tutorial on PROC LOGISTIC Arthur X. Li source 19
WUSS 2013 Customize Comparison Tables for Clinical Studies Polina Kukhareva,
Katherine J. Roggenkamp		 source 12
WUSS 2013 Decision Trees as a Predictive Modeling Method Gerry Hobbs source 8
WUSS 2013 How to Compute Custom Hazard Ratio in SAS (V8.2&V9.2) PHREG Procedure Liguo Cheng,
Yu Li		 source 8
WUSS 2013 Survival 101 - Just Learning to Survive Leanne Goldstein,
Rebecca Ottesen		 source 24
WUSS 2013 The Association of Morbid Obesity with Mortality and Coronary Revascularization among Patients with Acute Myocardial Infarction using ARRAYS, PROC FREQ and PROC LOGISTIC" Ashwini Erande,
Shaista Malik		 source 11
WUSS 2013 Tools for Imputing Missing Data Taylor Lewis source 16
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 Chi-Square and T-Tests Using SAS: Performance and Interpretation Jennifer L. Waller,
Maribeth H. Johnson		 source 12
SESUG 2013 Comparing SAS PROC MI and IVEware Callable Software Bruno Vizcarra,
Amang Sukasih		 source 11
SESUG 2013 Going from Zero to Report Ready with PROC TABULATE Rachel Straney source 12
SESUG 2013 Imputing Dose Levels for Adverse Events John R. Gerlach,
Igor Kolodezh		 source 8
SESUG 2013 SAS Macros to Conduct Common Biostatistical Analyses and Generate Reports Dana Nickleach,
Yuan Liu,
Adam Shrewsberry,
Kenneth Ogan,
Sungjin Kim		 source 8
SESUG 2013 What Do Your Consumer Habits Say About Your Health? Using Third-Party Data to Predict Individual Health Risk and Costs Satish Garla source 15
MWSUG 2013 A Tutorial on PROC LOGISTIC Arthur X. Li 19
MWSUG 2013 Analyzing Categorical Variables from Complex Survey Data Using PROC SURVEYFREQ Taylor Lewis 20
MWSUG 2013 Analyzing Continuous Variables from Complex Survey Data Using PROC SURVEYMEANS Taylor Lewis 14
MWSUG 2013 Improved Interaction Interpretation: Application of the EFFECTPLOT statement and other useful features in PROC LOGISTIC Robert G. Downer 8
MWSUG 2013 Reuse, Don't Reinvent: Extending Model Selection Using Recursive Macro Anca M Tilea,
Philip L Francis III		 5
NESUG 2013 Analyzing Continuous Variables from Complex Survey Data Using PROC SURVEYMEANS Taylor Lewis 15
NESUG 2013 The Ultimate Macro to Generate Summary Tables Lan Hu,
Xiaoqiang Wang		 12
PharmaSUG 2013 Combining Analysis Results from Multiply Imputed Categorical Data Bohdana Ratitch,
Ilya Lipkovich,
Michael O'Kelly		 source 19
PharmaSUG 2013 Imputing Dose Levels for Adverse Events John R. Gerlach,
Igor Kolodezh		 source 8
SGF 2013 A Flexible Method to Apply Multiple Imputation Using SAS/IML Studio Lisa M. Lix,
Xue Yao		 source
pdf		 9
SGF 2013 Chi-Square and T-Tests Using SAS: Performance and Interpretation Jennifer L. Waller,
Maribeth H. Johnson		 source 12
SGF 2013 Cox Proportional Hazard Model Evaluation in One Shot Polina Kukhareva source 11
SGF 2013 Estimating Harrell's Optimism on Predictive Indices Using Bootstrap Samples Irena Stijacic Cenzer,
W. John Boscardin,
Katharine Kirby,
Yinghui Miao		 source 12
SGF 2013 Extension Node to the Rescue of the Curse of Dimensionality via Weight of Evidence (WOE) Recoding Andrew Cathie,
Goutam Chakraborty,
Satish Garla		 source 9
SGF 2013 SAS Data Management Techniques: Cleaning and Transforming Data for Delivery of Analytic Data Sets Christopher W. Schacherer source 38
SGF 2013 The Surprisingly "Sym"ple Alternative to Hardcoding Rachel Carlson,
Ruchi Sharma		 source 6
SGF 2013 What Do Your Consumer Habits Say About Your Health? Using Third-Party Data to Predict Individual Health Risk and Costs Albert Hopping,
Rick Monaco,
Sarah Rittman,
Satish Garla		 source 15
SGF 2013 Where Should I Dig? What to Do Before Mining Your Data Stephanie R. Thompson source 3
NESUG 2012 Create User-Defined Formats: Using SAS Code to Write Code Yonghong Shang 11
SCSUG 2012 Dirty Data? Clean it up with SAS. Gabriela Cantu source 11
SCSUG 2012 SAS Data Management Techniques: Cleaning and Transforming Data for Delivery of Analytic Data Sets Christopher W. Schacherer source 38
PHUSE EU 2012 The Logic and Logistics of Logistic Regression, Including New Features in SAS 9.2 Lawrence Rasouliyan source
presentation source		 16
SESUG 2012 How to Perform and Interpret Chi-Square and T-Tests Jennifer L. Waller source 14
SESUG 2012 Multiple Imputation for Ordinal Variables: A Comparison of SUDAAN's PROC IMPUTE vs. PROC MI Multiple Imputation source 12
SESUG 2012 ODS Output Data Sets That Work for You Stuart D. Long,
Edward Heaton,
Daniel R. Scharf		 source 29
SESUG 2012 Where Should I Dig? What to Do Before Mining Your Data Stephanie R. Thompson source 3
MWSUG 2012 An Analysis of Diabetes Risk Factors Using Data Mining Approach Akkarapol Sa-ngasoongsong,
Jongsawas Chongwatpol		 11
MWSUG 2012 Creating a SAS Frequency Data Set of Valid Categorical Variables for Export to Microsoft Excel or Access Neil Kamdar 7
MWSUG 2012 Modeling Complex Survey Data Taylor Lewis 16
MWSUG 2012 SAS Data Management Techniques: Cleaning and Transforming Data for Delivery of Analytic Data Sets Christopher W. Schacherer 38
WUSS 2012 PROC FREQ Is More Than Just Simply Generating a 2-by-2 Table Wuchen Zhao source 11
WUSS 2012 SAS Rule-Based Codebook Generation for Exploratory Data Analysis Ross Bettinger source 8
WUSS 2012 Survival Analysis with PHREG: Using MI and MIANALYZE to Accommodate Missing Data Arthur L. Carpenter,
Christopher F. Ake		 source 7
SGF 2012 Beyond Binary Outcomes: PROC LOGISTIC to Model Ordinal and Nominal Dependent Variables Eric P. Elkin source 8
SGF 2012 Developing a Predictive Model for Customer Trip Purpose to Be Integrated into Enterprise Strategy and Analytics Jonathan Levine source 16
SGF 2012 Handling Missing Data by Maximum Likelihood Paul D. Allison source 21
SGF 2012 How to Perform and Interpret Chi-Square and T-Tests Jennifer L. Waller source 20
SGF 2012 SG Techniques: Telling the Story Even Better! Chuck Kincaid,
Jack E. Fuller		 source 14
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 Using SAS PROC MIXED to Fit Health Policy-Based Hierarchical Models Lori L. Miller,
Fred Wilds		 source 7
SESUG 2011 Analysis of a Binary Outcome Variable Using the FREQ and LOGISTIC Procedures Arthur X. Li source 18
SESUG 2011 Introduction to ODS Graphics for the Non-Statistician Mike Kalt,
Cynthia L. Zender		 source 28
SESUG 2011 Tailoring Logistic Regression Model Analyses with the ODDSRATIO Statement in PROC LOGISTIC Taylor Lewis source 8
SESUG 2011 Using SAS GTL to Visualize Your Data when there is Too Much of it to Visualize Perry Watts,
>>>>		 source 22
SESUG 2011 Using SAS GTL to Visualize Your Data when there is Too Much of it to Visualize Perry Watts,
>>>>		 source 22
WUSS 2011 SAS Procedure Proc Mixed to Assess the Effects of School Health Policy Requirements on Change in Student Health Outcomes Lori Miller source 9
WUSS 2011 Using SAS GTL to Visualize Your Data when there is Too Much of it to Visualize Nathaniel Derby source 22
WUSS 2011 What's happening if there is "B" in the general linear modeling output? Jason Shilong Kuang source 5
WUSS 2011 Why Dummy Variable Makes You SMART, and How to Do it SEXY Brian Sun source 12
MWSUG 2011 A Lazy Programmer's Macro for Descriptive Statistics' Tables Matthew C. Fenchel,
Gary L. McPhail,
Rhonda D. VanDyke		 11
MWSUG 2011 Before Logistic Modeling - A Toolkit for Identifying and Transforming Relevant Predictors Steven Raimi,
Bruce S. Lund		 18
MWSUG 2011 Increased Life Expectancy from Positive Perceptions of Retirement Reuben Ng,
Deepak C. Lakra,
Becca R. Levy		 10
MWSUG 2011 Using SAS GTL to Visualize Your Data when there is Too Much of it to Visualize Perry Watts,
Nathaniel Derby		 22
NESUG 2011 Using SAS GTL to Visualize Your Data when there is Too Much of it to Visualize Perry Watts,
Nathaniel Derby		 22
PharmaSUG 2011 Implementation of Pattern-Mixture Models Using Standard SAS/STAT Procedures Bohdana Ratitch,
Michael O'Kelly		 source 10
SGF 2011 Bump Hunting With SAS: A Macro Approach to Employing PRIM Jennifer Sniadecki source 9
SGF 2011 Introduction to ODS Graphics for the Non-Statistician Mike Kalt,
Cynthia L. Zender		 source 28
SGF 2011 ODS Output Data Sets That Work for You Stuart D. Long,
Edward Heaton,
Daniel R. Scharf		 source 29
SGF 2011 Taking Disease and Health Management Analytics into the Next Generation George S. Habek source 13
SGF 2011 The Anti-Curse: Creating an Extension to SAS Enterprise Miner Using PROC ARBORETUM Andrew S. Cathie source 11
SGF 2011 To FREQ, Perchance to MEANS Christopher J. Bost source 10
SGF 2011 Visualizing Marginal Effects from Interactions in Generalized Linear Models Xiao Chen,
Brigid Wilson		 source 7
NESUG 2010 Survey Analysis: Options for Missing Data Paul Gorrell 10
NESUG 2010 To FREQ, Perchance to MEANS Christopher J. Bost 11
WUSS 2010 An Introduction to Statistical Tests for the SAS Programmer Sara Beck source 10
WUSS 2010 Decision Trees as a Predictive Modeling Method Gerry Hobbs source 7
WUSS 2010 Dummy Coding for Dummies Kathryn Martin source 10
WUSS 2010 Statistical Analysis - The First Steps Jennifer L. Waller source 20
WUSS 2010 Survival Analysis with PHREG: Using MI and MIANALYZE to Accommodate Missing Data Christopher F. Ake source 7
WUSS 2010 Where's The Match? Matching Cases and Controls after Data Collection Jennifer L. Waller source 6
MWSUG 2010 An Introduction to Multiple Imputation of Complex Sample Data Using SAS 9.2 Patricia A. Berglund 12
MWSUG 2010 Exploring, Analyzing, and Summarizing Your Data: Choosing and Using the Right SAS Tool from a Rich Portfolio Douglas Thompson 25
MWSUG 2010 Survival Analysis with PHREG: Using MI and MIANALYZE to Accommodate Missing Data Christopher F. Ake,
Arthur L. Carpenter		 6
SESUG 2010 Developing a Model for Person Estimation in Puerto Rico for the 2010 Census Coverage Measurement Program Colt S. Viehdorfer source 12
SESUG 2010 PROC_CODEBOOK, Automating the Review and Documentation of SAS Files James Terry source 3
SESUG 2010 Statistical Analysis - The First Steps Jennifer L. Waller source 20
PharmaSUG 2010 An Overview of the CLASS, CONTRAST, and HAZARDRATIO Statements in the SAS 9.2 PHREG Procedure Paul T. Savarese,
Michael J. Patetta		 23
SGF 2010 An Introduction to Multiple Imputation of Complex Sample Data Using SAS 9.2 Patricia A. Berglund source 12
SGF 2010 An Overview of the CLASS, CONTRAST, and HAZARDRATIO Statements in the SAS 9.2 PHREG Procedure Paul T. Savarese,
Michael J. Patetta		 source 23
SGF 2010 Data Simulation for Piloting Clinical Trials Display Programs Brandon L. Welch,
Rita Slater		 source 9
SGF 2010 Improving Your Statistical Consulting Prowess by Adding R to Your SAS Repertoire Mark Austen,
Jeffrey M. Gossett,
Maria S. Melguizo,
Chan-Hee Jo		 source 11
SGF 2010 Practicalities of Using ESTIMATE and CONTRAST Statements David J. Pasta source 20
SESUG 2009 Customer Retention Predictive Modeling in HealthCare Insurance Industry Jin Su,
Kimberly Cooper,
Tina Robinson,
Brad Jordan		 source 8
MWSUG 2009 Dietary Glycemic Load and Risk of Colon Cancer: A Guide to Data Management Svetlana Zelenskiy,
Lauren Byrne,
Cheryl L. Thompson,
Thomas C. Tucker,
David Bruckman,
Li Li		 16
PNWSUG 2009 Building Multiple Linear Regression Models - Food for Thought Colleen E. McGahan,
Mei Chong		 11
NESUG 2009 Survey Analysis: Options for Missing Data Paul Gorrell 11
WUSS 2009 Automating the Process of Scoring a Generalized Linear Model Fitted using PROC GENMOD Prakash Gurumurthy source 9
PharmaSUG 2009 Customized Efficient Data-Driven SAS Based System Tailored To Clients Needs Mila Chiflikyan,
Mai Nguyen,
Renee Karlsen		 12
SGF 2009 Bubble, Bubble: Less Toil, No Trouble Wendy B. Dickinson,
Bruce W. Hall,
Constance Hines		 source 10
SGF 2009 Learning When To Be Discrete: Continuous vs. Categorical Predictors David J. Pasta source 10
SGF 2009 The Basics of Experimental Design for Multivariate Analysis Steve Figard source 15
SGF 2009 Tips and Tricks for Creating the Reports Your Clients Need to See Michael J. Molter source 13
WUSS 2008 Learning When To Be Discrete: Continuous vs. Categorical Predictors David J. Pasta source 6
MWSUG 2008 Imputation of Categorical Missing Data: A comparison of Multivariate Normal and Multinomial Methods Holmes Finch,
Matt Margraf		 12
NESUG 2008 An Introduction to the SAS Survey Analysis PROCs Xiuhua Chen,
Paul Gorrell		 17
NESUG 2008 Get into the Groove with %SYSFUNC: Generalizing SAS Macros with Conditionally Executed Code Kathy Hardis Fraeman 8
PharmaSUG 2008 Automated SAS Macro for Adverse Event Logistic Regression Analysis Suhas R. Sanjee 8
PharmaSUG 2008 The Logic and Logistics of Logistic Regression Lawrence Rasouliyan,
Dave P. Miller		 14
SGF 2008 PROC CORRESP for Categorical Data: Correspondence Analysis (CA) for Discovery, Display, and Decision-Making Wendy B. Dickinson,
Bruce W. Hall		 source 8
SGF 2008 Using PROC GENMOD to find a fair house insurance rate for the Norwegian market Sverre Grevskott,
Sten Sture		 source 9
NESUG 2007 Customizing Output for Regression Analyses Using ODS and the Data Step Zhenyi Xue 11
NESUG 2007 PROC LOGISTIC: The Logistics Behind Interpreting Categorical Variable Effects Taylor Lewis 7
NESUG 2007 Tips and Tricks for Creating the Reports Your Clients Need to See Mike Molter 13
NESUG 2007 Using SAS ODS to Extract and Merge Statistics from Multiple SAS Procedures into a Single Summary Report, a Detailed Methodology Stuart D. Long,
Jeffrey M. Abolafia,
Lawrence Park		 22
NESUG 2007 Variable Selection and Variable Transformations in SAS Enterprise Miner 5.2 Kattamuri S. Sarma 12
SESUG 2007 Analyzing Large Social Networks with MP Connect, SAS/IntrNet, and %DS2CONST Shane L. Hornibrook source 7
SESUG 2007 Application of an Exact Covariate Matching Macro in Outcome Analysis Guiping Yang source 19
MWSUG 2007 Identifying and Overcoming Common Data Mining Mistakes Doug Wielenga 20
MWSUG 2007 SAS Macros for Quick Summary Reporting and Uppercasing of All Variables Craig Balog 4
MWSUG 2007 Using Data Mining Techniques to Predict Student Development and Retention Morgan C. Wang 59
WUSS 2007 An Example of SAS Application in Public Health Research --- Predicting Smoking Behavior in Changqiao District, Shanghai, China Ding Ding source 8
WUSS 2007 Data Mining Using SAS Enterprise Miner Randall Matignon source 10
WUSS 2007 Health Outcomes Research Using Time-to-Event Analytic Approaches Tyler C. Smith,
Besa Smith		 source 22
WUSS 2007 Recreating the SELECTION=SCORE Model Specification with the BEST=n Effect Selection Option for PROC SURVEYLOGISTIC Sara R. Adams,
David R. Mink,
Dave P. Miller		 source 8
PNWSUG 2007 Missing Data? A Look at Two Imputation Methods Anita Rocha 8
PharmaSUG 2007 A Review of Propensity Score Application in Healthcare Outcome and Epidemiology Guiping Yang 24
PharmaSUG 2007 A SAS Macro for Rapid Checking the Data Records Heng Zou 8
PharmaSUG 2007 Saving QC Time for Production Tables Linfeng Xu,
Sunil Kumar Gupta		 10
SGF 2007 Categorizing Drug Data in a Complex Survey with SAS PROC FORMAT, INPUT, and PUT Functions Henry H. Xia source 8
SGF 2007 Identifying and Overcoming Common Data Mining Mistakes Doug Wielenga source 20
SGF 2007 SAS Macros for Automated Model Selection When the Response Variable Is Nominal-Needs and Solutions Involving PROC CATMOD Bonnie E. Williams,
Todd Kegan		 source 12
SGF 2007 Text Mining and PROC KDE to Rank Nominal Data Patricia B. Cerrito source 21
PHUSE EU 2006 Save Time: Program Your Output Specs Hansjörg Frenzel,
James Witt		 source 11
PHUSE EU 2006 The Hazards of Modelling Proportional Hazards in SAS Erika Daly,
Farzana Sufi		 source 4
SESUG 2006 Analyzing Large Social Networks with MP Connect, SAS/IntrNet, and %DS2CONST Shane L. Hornibrook source 7
SESUG 2006 Using SAS ODS to Extract and Merge Statistics from Multiple SAS Procedures into a Single Summary Report, a Detailed Methodology Stuart D. Long source 21
WUSS 2006 Clean Up Your Act: Data Cleaning with SAS Mel Widawski source 9
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 Get the Correct Hazard Ratio from SAS PROC PHREG Procedure Betty Ying Wang source 7
WUSS 2006 The Logic and Logistics of Logistic Regression Lawrence Rasouliyan,
Dave P. Miller		 source 14
PharmaSUG 2006 %SummaryTable: A SAS Macro to Produce a Summary Table in Clinical Trial Yinmei Zhou,
St. Jude Children's		 7
PharmaSUG 2006 PROC FORMAT is Our Friend Erin M. Christen 20
SUGI 2006 %DataAutoSum: A SAS Macro for Automatically Producing a Customized Clinical Data Summary Report Deqing Pei,
Cheng Cheng		 source 8
SUGI 2006 Comparison of Data Preparation Methods for Use in Model Development with SAS Enterprise Miner Charles Manahan source 10
SUGI 2006 Using SAS ODS to Extract and Merge Statistics from Multiple SAS Procedures Stuart D. Long,
Jeffrey M. Abolafia,
Lawrence Park		 source 21
WUSS 2005 Graphing the Probability of Event as a Function of Time Using Survivor Function Estimates and the SAS System's PROC PHREG Tyler C. Smith,
Besa Smith		 source 18
NESUG 2005 %DIAGNOS: a Macro for a Quick Look Into the Inside of Your Data Set Yin You 3
NESUG 2005 Algorithm and Software for Yield Analysis Igor Mandel,
Victor Kamensky		 16
NESUG 2005 Predictive Modeling Using Survival Analysis Vadim Pliner 10
PharmaSUG 2005 Generating Customized Analytical Reports from SAS Procedure Output Brinda Bhaskar,
Kennan Murray		 9
PharmaSUG 2005 Remembering the Past: Ensuring Quality though Historical Benchmarking Marc-Paul Lee 8
SUGI 2005 Parameterizing Models to Test the Hypotheses You Want: Coding Indicator Variables and Modified Continuous Variables David J. Pasta source 20
SUGI 2005 Predicting Workers' Compensation Insurance Fraud Using SAS Enterprise Miner 5.1 and SAS Text Miner Terry J. Woodfield source 6
SUGI 2005 Rounding after Multiple Imputation with Non-Binary Categorical Covariates Christopher F. Ake source 11
SUGI 2005 Using SAS to Estimate Proportional Odds Ratio Model for Meta-Analysis of Diagnostic Tests Mir S. Siadaty,
Jianfen Shu		 source 10
NESUG 2004 Analyzing Complex Survey Data: Some SAS-SUDAAN Comparisons Xiuhua Chen,
Paul Gorrell		 15
NESUG 2004 Generating Customized Analytical Reports from SAS Procedure Output Brinda Bhaskar,
Kennan Murray		 12
SESUG 2004 Where's The Match? Jennifer L. Waller,
Verna C. Brantley,
Robert H. Podolsky		 source 6
WUSS 2004 Beyond Binary Outcomes: PROC LOGISTIC to Model Ordinal and Nominal Dependent Variables Eric P. Elkin source 8
WUSS 2004 Creating Custom Tables Using SAS Tyler Cole source 11
WUSS 2004 Kaplan Meier And Cox Proportional Hazards Modeling: Hands On Survival Analysis Tyler C. Smith,
Besa Smith		 source 14
WUSS 2004 Parameterizing Models to Test the Hypotheses You Want: Coding Indicator Variables and Modified Continuous Variables David J. Pasta source 12
WUSS 2004 The Continuing Quandary of Survey Data Part II:Comparison of SAS Procedures and SUDAAN Procedures Katherine L. Baisden source 20
WUSS 2004 Using Classification Tree Outcomes to Enhance Logistic Regression Models Tim Millard source 4
PharmaSUG 2004 %Cox_PH - An enhancement of SAS PROC PHREG Hong (Lily) Zhang,
Robin Mogg		 8
PharmaSUG 2004 A Macro Generating a Report-Ready Table in Different Layout and Format Renda Cheng 12
PharmaSUG 2004 Tools to Facilitate the Creation of Pooled Clinical Trials Databases Patricia Majcher 8
WUSS 2003 Taming Your Metadata Part I: Getting data dictionary and codebook from your SAS databases Peter Godard source 6
SEUGI 2003 Text Mining for tourism - The world of typical high quality restaurants in Piedmont [presentation] Roberto Fontana source 78
PharmaSUG 2003 Capabilities and Example Uses of a SAS Macro for Summary Reporting of Clinical Data James T. Decker,
Jun Wang		 8
PharmaSUG 2003 SQL for People Who Don't Think They Need SQL Erin M. Christen 8
SUGI 2003 Continuous or Not: How One Can Tell Vatsala V. Karwe source 2
SUGI 2003 P-Value Generation Simplified with a Single SAS Macro Christopher S. Hord,
Peter J. Anderson		 source 3
NESUG 2002 An Automated Reporting Macro to Create Cell Index - An Enhanced Revisit Shi-Tao Yeh 5
WUSS 2002 Doing Big Demographic Segmentation with the Combination of Multivariate Procedures and Macro Facilities Charles Sun source 6
WUSS 2002 Doing More with Proce FREQ Using Options and ODS Richard Severino source 13
WUSS 2002 Imputation Strategies for Sexual Orientation Using SAS PROC MI Jesse Albert Canchola,
Joe Catania,
Torsten Neilands		 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
SUGI 2002 Predicting Customer Churn in the Telecommunications Industry - An Application of Survival Analysis Modeling Using SAS Junxiang Lu source 6
SUGI 2002 To Neural or Not to Neural? - This Is the Question Leon L. Fedenczuk source 6
WUSS 2001 What about a PROC RATES for All of Your Rates and Proportions Needs? Tyler C. Smith,
Besa Smith,
Margaret A. K. Ryan		 source 6
SEUGI 2001 The SAS Text Mining Solution [presentation] Bernd Drewes,
Wayne Thompson		 source 22
SUGI 2001 Input File Cleaning and Screening Using a SAS Macro Mike D. Tangedal source 7
SCSUG 2000 The Use of PROC MIXED for Analyzing Cohort-Sequential Designs C. Nathan Marti 11
SESUG 2000 A High-Level Summary Table Generation Language Supplying the Missing Link between PROC MEANS using a CLASS Statement and PROC TABULATE Dorothy E. Pugh source 9
SESUG 2000 Using Data Mining Technology to Identify and Prioritize Emerging Opportunities for Mortgage Lending to Homeownership-Deficient Communities Mortgage Lending source 10
NESUG 2000 A New Method Of Look-Up For A Large Medmart System Edward Aronov 3
NESUG 2000 Macro Makes PROC MEANS Flexible Kimberly D. Yarbrough 2
WUSS 2000 PROC FREQ: It's More Than Counts Richard Severino source 10
SEUGI 2000 Development of Micro-Aggregation System for Confidential Data [presentation] L. Bechet,
P. Loosveldt,
T. Le Tri		 source 44
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
PharmaSUG 2000 An Alternative to the Odds Ratio: A Method for Comparing Adjusted Treatment Group Effects on a Dichotomous Outcome P. Chris Holland 5
PharmaSUG 2000 Using SAS Macro to List the Frequencies and Statistics in a Summary Table Kinwah Fung,
Toronto Sunnybrook		 6
SUGI 2000 PROC FREQ: It's More Than Counts Richard Severino source 10
NESUG 1999 Effective Methods for Graphical Analysis of Quantitative and Categorical Survey Variables Donald T. Gantz 10
SUGI 1999 The Science and Art of Market Segmentation Using PROC FASTCLUS Mark E. Thompson source 5
SUGI 1999 Using SAS Macro to Include Statistics Output in Clinical Trial Summary Table Amy C. Young,
Sharon X. Zhou		 source 5
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
NESUG 1998 A Smart Guide to Dummy Variables: Four Applications and a Macro Susan B. Garavaglia 10
SESUG 1998 Programmatic Generation of Table Specifications Using the SAS Macro Facility Weimin "WilHam" Sun,
Caroline Stewart		 10
PNWSUG 1998 The Science and Art of Market Segmentation Using PROC FASTCLUS Mark E. Thompson 6
SEUGI 1998 Defining groups of "typical investors": hierachical clustering for qualitative data Raffaela Piccarretta source 7
SCSUG 1997 A Generalization of the Stuart-Maxwell Test Stephen I. Black,
Mithat Gonen		 14
SUGI 1997 Creating Clinical Trial Summary Tables Containing P-Values: A Practical Approach Using Standard SAS Macros Jun Zuo,
Carl R. Haske		 source 6
SUGI 1997 Developing Risk Adjustment Techniques Using the SAS System for Assessing Health Care Quality in the IMSystem Yanchun Xu,
Andrius Kubilius		 source 5
SUGI 1997 Generic Methodology in Report Building by Using SAS Macros Irene Zhao source 5
SUGI 1997 Introduction to Building a Linear Regression Model Leslie A. Christensen source 7
NESUG 1996 A Data Warehous/Business Intelligence Facility: Success in an Insurance Company John Gilbert 10
NESUG 1996 Macros Developed for Statistical Summary and Tabulation of Clinical Data William Sun,
David Lago,
David Handelsman,
Jack Shostak		 10
SUGI 1996 New Age Marketing: Past Life Regression vs. LogisticRegression C. Olivia Parr Rud source 5
SUGI 1996 Pairwise Matching of Sample and Control Groups Using PROC FASTCLUS Kathleen A. Travis,
Stephan Arndt,
Nancy C. Andreasen		 source 5
SESUG 1995 New Age Marketing: Past Life Regression versus Logistic Regression C. Olivia Parr Rud 9
SUGI 1995 A Comparative Evaluation of Selected Statistical Software for Computing Various Categorical Analyses Nancy McDermott,
Cynthia White		 source 6
NESUG 1994 Using of the PHREG Procedure in a Matched Case-Control Analysis Karin LaPann 4
SESUG 1994 Managing Overkill: How to Use SAS PROC CA TMOD to Estimate Odds Ratios Sigurd W. Hermansen 5
SEUGI 1994 Graphical Extensions for Principal Component Analysis (Insight of a Dream PCA) Philippe Besse source 16
SUGI 1994 SAS/PH-Clinical Software: Study Startup Hints Juliana M. Ma,
Sandra D. Schlotzhauer		 source
NESUG 1993 An Overview of Methods Available For Obtaining Frequency Counts of Categorical Data Lawerence P. Specht 10
SEUGI 1993 Extensions to Multivariate Descriptive Analysis Yves Roy source 14
SEUGI 1993 Generalised Linear Model and Correspondence Analysis. Application to the Goitre Problem in Mali Michel Tenehaus source 28
SUGI 1993 A Broadly Applicable Statistical Program (BASP) for the Preparation and Analysis of Longitudinal Data Sets Susan Y.J. Zhou,
Lawrence A. Kingsley,
Sheila S. H. Leung,
Patricia S. Wehman		 source 6
SUGI 1993 Planning, Preparing, Documenting, and Referencing SAS Products RoJeanne Liu,
Arthur Foreman		 source 6
MWSUG 1992 Marketing Research: Uncovering Competitive Advantages Warren F. Kuhfeld 9
SEUGI 1992 Cluster Characterisation wit the SAS System Factorial Analysis Solves the Problem of Synthesis Data and hte Typology of Clustering Method Christian Derquenne source 17
SEUGI 1992 Marketing Research - Uncovering Competitive Advantage Gerhard Held source 8
SUGI 1992 Marketing Research: Uncovering Competitive Advantages Warren F. Kuhfeld source 9
MWSUG 1991 Home Value - Location, Location, Location: An Application in Real Property Gloval Response Surface Technology Lawrence C. Marsh,
Anthony B. Sindone		 5
SEUGI 1991 Inferences Control in Data Bases A. Bekhechi source 8
NESUG 1990 Exact Nonparametric Inference: Theory, Applciations and Software Cyrus R. Mehta 16
SUGI 1989 An Expert Systems Application for Selecting Statistical Techniques Clyde Dent,
Ray Palmer,
Eric Yu I. Wang		 source 3
SEUGI 1988 Automatic Analysis of Clinical Trials J. C. Peyrieux source 6
SUGI 1986 PROC TABULATE as a Tool for Categorical Analysis Tamara R. Fischell,
Juliana M. Ma		 source 5
SUGI 1985 Descriptive Statistics: Using Indicator Variables Tamara R. Fischell,
Juliana M. Ma		 source 5
SEUGI 1984 New Statistical Features in SAS Gerhard Held source 13
SUGI 1984 PROC SUMMARY as the Basis for Efficient Analyses of Large Files Carol Leininger,
Juliana M. Ma		 source 4
SUGI 1982 Variable Selection for Categorical Data Using SAS Erik J. Bergstralh,
Susan McGorray		 source 6

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