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388 papers and 12 presentations; 350 titles.

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Conference × Year × Title × Authors Extras Pages
WUSS 2026 The GENMOD Toolkit: What do you do when things aren't Normal? [presentation] Danny R. Modlin source 36
PharmaSUG CN 2026 An Integrated, AI-Augmented R Shiny Platform for Oncology Clinical Trial Decision Intelligence: From CDISC Data to Go/No-Go in One Unified Hub Zhiping Yan source 28
PharmaSUG CN 2026 TFL Generation Using R: Negative Binomial Regression Implementation and Comparison with SAS Ye Sun,
Jianchang Hu		 source 11
PharmaSUG 2026 Contrast Effects in Curated Observational Data Shankar Srinivasan,
Helen Guo,
Yvonne Buttkewitz		 source 16
PHUSE APAC 2026 Beyond Toxicity : Accelerating Dose -Finding with Pharmacokinetic -Driven Bayesian Design PKBOIN-12 Anetta Mary Xavier source
presentation source		 13
PHUSE APAC 2026 Estimation of the Hypothetical Estimands using Longitudinal version of the TMLE Shreya Wahi source
presentation source		 8
PHUSE APAC 2026 From Data to Digital Phenotypes: Modelling High-Dimensional PROs and Actigraphy Data in Decentralized Psychiatric Trials Sakshi Kaushik source
presentation source		 14
PHUSE EU 2025 GLMM and GEE for Categorical Repeated Measures - Linking SAS and R Miriam Amor source
presentation source		 16
PHUSE EU 2025 Multiple Imputations Overview of Missing Data Problem, Solution Methods and SAS Implementation Dmytro Kalinin source
presentation source		 13
MWSUG 2025 An analysis of Emergency Department Visits for the 10 Health Division Regions across the US during the period 2018 2025 [presentation] Baoyuan Zhou source 24
SESUG 2025 Efficacy + Safety in Phase 1/2 Immunotherapy Oncology Trials: OBD vs. MTD Ron Smith 8
SESUG 2025 Introduction to Data Simulation Jason Brinkley 10
SESUG 2025 The GENMOD Toolkit: What do you do when things aren't Normal? Danny R. Modlin 36
WUSS 2025 The GENMOD Toolkit: What do you do when things aren't Normal? [presentation] Danny R. Modlin source 36
PharmaSUG 2025 Calculating exact posterior probabilities and credible intervals from Bayesian borrowing robust mixture priors for binary, count and continuous outcomes in R and SAS Darren Scott,
Armando Turchetta		 source 20
PharmaSUG 2025 Clopper Pearson CI? get your data ready for it! Ruth Marisol Rivera Barragan,
Isaac Vazquez		 source 7
PharmaSUG 2025 How to compute common clinical trials statistics in R Oleksandr Babych source 15
PHUSE US 2025 Predictive Analytics for Adverse Event Underreporting Steven A. Gilbert source
presentation source		 10
MWSUG 2024 What if Proc Power Can't Help? Calculating Power via Simulation, Example with Count Regression Brandy R. Sinco,
Joceline Vu,
Pasithorn Suwanabol		 source 16
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 Special Control Charts for Rare Events: G-charts and T-charts Melvin T. Alexander source 15
SESUG 2024 Streamlining Vaccine Study Output Generation with a Versatile Efficacy Macro Zhengyang Shi source 6
PharmaSUG CN 2024 Application of I&I Late Phase in Programming Renxiang Wang source 15
PharmaSUG CN 2024 Sample size calculation for comparing two groups of count data in clinical trials Lijuan Lin source 8
PharmaSUG 2024 Bayesian Models with the Power Prior Using PROC BGLIMM Yi Gong,
Fang K. Chen		 source 15
PharmaSUG 2024 Generative Artificial Intelligence in sample size estimation - challenges, pitfalls, and conclusions Igor Goldfarb,
Vikas Sharma		 source 26
WUSS 2023 Let's Get FREQy with our Statistics: Data-Driven Approach to Determining Appropriate Test Statistic Richann J. Watson,
Lynn Mullins		 source 14
SESUG 2022 A SAS Macro for Implementing a Nonparametric Control Charting Scheme for Individual Observations Austin R. Brown source 11
PharmaSUG 2022 An Expanded Set of SAS Macros for Calculating Confidence Limits and P-values Under Simon's Two-Stage Design Accounting for Actual and Planned Sample Sizes Mikhail Melikov,
Alex Karanevich		 source 8
SESUG 2021 A Macro to Utilize a Nonparametric Multiple Stream Process Quality Control Chart in SAS Austin R. Brown source 10
PHUSE US 2021 A Bayesian Approach to Detection of Treatment-related Effects in Toxicology Studies by Borrowing Information from Historical Control Animals [presentation] Kevin Snyder,
Md Yousuf Ali		 source
video		 15
PharmaSUG 2021 Shiny decisions - An R-shiny application for decision frameworks Lasse Nielsen source 6
SGF 2021 Bayesian Analysis of GLMMs Using PROC BGLIMM Walter W. Stroup source
pdf		 25
PHUSE EU 2020 Re-scaling Weights to Effective Sample Size [presentation] Andrea Parodi,
Dimitri Petratchenko		 source
video		 25
SESUG 2020 Custom SAS Studio Tasks for All Occasions John Stephen Taylor source 10
SESUG 2020 Model Comparison of Machine Learning Techniques to detect signs of Penetrating Abdominal and Pelvic Injuries using Base JMP and R Integration Melvin T. Alexander source 25
SESUG 2020 Using GENMOD to Calculate Prevalence Ratio for Concussion and Suicidal behaviors among U.S. High School Students Abbas S. Tavakoli source 13
SGF 2020 Analyzing Non-normal Data: Application to Missing Data Problems Niloofar Ramezani source 10
SGF 2020 Bayesian Sequential Monitoring of Clinical Trials Using SAS Matthew A. Psioda source 13
SGF 2020 Fitting Statistical Models with PROC MCMC Mark Ghamsary source 26
SGF 2020 Model-Based Risk-Adjustment in Clinical Outcome Research Jiming Fang,
Feng Qiu		 source 10
SGF 2020 Piecewise Latent Growth Curve Models to Test for Discontinuities in Disease Prevalence Trends Lin Yan source 10
SGF 2020 Testing Hypotheses for Equivalence and Non-inferiority with Binary and Survival Outcomes Joseph C. Gardiner source 23
SGF 2020 Time After Time: D-I-D and ITS Models in SAS Margaret Warton source 21
PharmaSUG 2020 %MVMODELS: a Macro for Survival and Logistic Analysis Jeffrey P. Meyers source 23
PharmaSUG 2020 A SAS Macro for Calculating Confidence Limits and P-values Under Simon's Two-Stage Design Alex Karanevich,
Michael Ames		 source 5
PharmaSUG 2020 Demographic Table and Subgroup Summary Macro %TABLEN Jeffrey P. Meyers source 12
PharmaSUG 2020 Effective Exposure-Response Data Visualization and Report by Combining the Power of R , SAS programming and VBScript Shuozhi Zuo,
Hong Yan		 source 11
PharmaSUG 2020 Implementing Quality Tolerance Limits at a Large Pharmaceutical Company Steven A. Gilbert source 13
PHUSE EU 2019 Dose-finding Schemes in Clinical Trials Michael Brockmann source
presentation source		 15
SESUG 2019 Advanced Statistical Modeling within Machine Learning and Big Data Analytics Niloofar Ramezani,
George Mason		 source 16
SESUG 2019 Regression Models for Count Data Jason Brinkley source 8
MWSUG 2019 Sample Size and Design Considerations in Studies Assessing Non-Inferiority using Continuous Outcomes Michael G. Wilson 19
PharmaSUG 2019 %LOGBINAUTO: A SAS 9.4 Macro for Automated Forward Selection of Log-Binomial Models Matthew Finnemeyer source 12
PharmaSUG 2019 Sample Size Determination with SAS Studio Bill Coar source 13
SGF 2019 Introducing the BGLIMM Procedure for Bayesian Generalized Linear Mixed Models Amy Shi,
Fang K. Chen		 source 20
SGF 2019 Sample Size Determination with SAS Studio William Coar source 13
SGF 2019 The Categorical Might of PROC FREQ Jinson J. Erinjeri,
Saritha Bathi		 source 18
SGF 2019 Zero-Inflated and Zero-Truncated Count Data Models with the NLMIXED Procedure Robin High source 18
PHUSE US 2019 Using Count-based Statistical Models for Key Performance Indicators, Risk Metrics, etc. [presentation] Aaron Mackey source 15
PHUSE EU 2018 Implementing Advanced Analytics and Machine Learning in Risk-based Strategies Rajneesh Patil source
presentation source		 3
SESUG 2018 A Flexible Approach to Computing Bayes' Factors with PROC MCMC Tyler Hicks source 9
SESUG 2018 Introduction to Data Simulation Jason Brinkley source 9
SESUG 2018 Let's Get FREQy with our Statistics: Data-Driven Approach to Determining Appropriate Test Statistic Richann J. Watson,
Lynn Mullins		 source 14
SESUG 2018 Regression Models for Count Data Jason Brinkley source 8
SESUG 2018 The Categorical Might of PROC FREQ Jinson J. Erinjeri,
Saritha Bathi		 source 18
WUSS 2018 Let's Get FREQy with our Statistics: Data-Driven Approach to Determining Appropriate Test Statistic Richann J. Watson,
Lynn Mullins		 source 14
WUSS 2018 Oops, I D-I-D It Again! Advanced Difference-in-Differences Models in SAS Margaret Warton,
Melissa Parker		 source 17
PHUSE US 2018 Modeling and Text Analysis to Empower FAERS Adverse Event Mitigation Qais Hatim,
Emily McRae		 source
presentation source		 24
PharmaSUG 2018 A SAS@ Macro Application on Confidence Intervals for Binominal Proportion Kaijun Zhang,
Sheng Zhang		 source 13
PharmaSUG 2018 Let's Get FREQy with our Statistics: Data-Driven Approach to Determining Appropriate Test Statistic Lynn Mullins,
Richann J. Watson		 source 14
PharmaSUG 2018 Statistician in my Soul. Statistical Questions from SPA Nadiia Hryhorenko source 12
SGF 2018 Alternative Variance Parameterizations in Count Data Models Robin High source 14
SGF 2018 Insights into Using the GLIMMIX Procedure to Model Categorical Outcomes with Random Effects Kathleen Kiernan source 23
SGF 2018 Let's Get FREQy with our Statistics: Data-Driven Approach to Determining Appropriate Test Statistic [presentation] Lynn Mullins,
Richann J. Watson		 source 24
SGF 2018 Using SAS Visual Investigator to Enforce Model Tuning Best Practices in a Regulatory Environment Scott Wood source 15
SESUG 2017 Applying Logistics Regression to Forecast Annual Organizational Retirements Alan Dunham source 12
SESUG 2017 Finding the Gold in Your Data: An Overview of Data Mining David A. Dickey source 25
SESUG 2017 Meta-Analysis and Matrix Multiplication: Adapting an IML-Based Macro for DerSimonian and Laird's Error Calculation to use Base SAS Venita DePuy source 16
PHUSE EU 2017 Adverse Events Data Over Time Kriss Harris source
presentation source		 11
PHUSE EU 2017 Power Calculation in a Multi-Stage Design, Following the Main Endpoint, A Binomial DIstribution Antonio Nieto,
Javier Gómez		 source
presentation source		 4
MWSUG 2017 Let's Get FREQy with our Statistics: Let SAS Determine the Appropriate Test Statistic Based on Your Data Lynn Mullins,
Richann J. Watson		 14
MWSUG 2017 Unconventional Statistical Models with the NLMIXED Procedure Robin High 14
WUSS 2017 Standardized Approaches for Analyzing Quality Improvement Interventions in Healthcare Settings Polina Kukhareva source 20
WUSS 2017 Step Up Your Statistical Practice with Today's SAS/STAT Software Robert N. Rodriguez source 19
PharmaSUG 2017 Adverse Event Data over Time Kriss Harris source 11
SGF 2017 %SURVEYGENMOD Macro: An Alternative to Deal with Complex Survey Design for the GENMOD Procedure Alan Ricardo da Silva source 28
SGF 2017 A Practical Guide to Getting Started with Propensity Scores Thomas Gant source 10
SGF 2017 Accelerate your SAS Programs with GPUs Henry Bequet,
Huina Chen		 source 9
SGF 2017 Fitting a Flexible Model for Longitudinal Count Data Using the NLMIXED Procedure Darcy Morris source 6
SGF 2017 Fitting Complex Statistical Models with NLMIXED and MCMC Procedures Robin High source 14
SGF 2017 Microservices and Many-Task Computing for High-Performance Analytics Henry Bequet source 7
SGF 2017 PROC LOGISTIC: Using New SAS 9.4 Features for Cumulative Logit Models with Partial Proportional Odds Paul Hilliard source
zip
pdf		 16
SGF 2017 Step Up Your Statistical Practice with Today's SAS/STAT Software Robert N. Rodriguez,
Phil Gibbs		 source 19
SESUG 2016 Analyzing non-normal data with categorical response variables Niloofar Ramezani,
Allameh Tabataba'i		 source 9
SESUG 2016 Introduction to Data Simulation Jason Brinkley source 8
SESUG 2016 Sample Size Estimation with PROC FREQ and PROC POWER Adeline J. Wilcox source 12
SESUG 2016 Statistical Model Building for Large, Complex Data: Five New Directions in SAS/STAT Software Robert N. Rodriguez source 23
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 Constructing Confidence Intervals for the Differences of Binomial Proportions in SAS William Garner source 13
WUSS 2016 Equivalence Tests John Amrhein,
Fei Wang		 source 9
WUSS 2016 Fitting Your Favorite Mixed Models with PROC MCMC Fang K. Chen source 27
WUSS 2016 Introducing the HPGENSELECT Procedure: Model Selection for Generalized Linear Models and More Robert N. Rodriguez source 18
WUSS 2016 Statistical Model Building for Large, Complex Data: Four New Directions in SAS/STAT Software Robert N. Rodriguez source 23
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 Everything or Nothing - A Better Confidence Intervals for Binomial Proportion in Clinical Trial Data Analysis Sakthivel Sivam,
Subbiah Meenakshisundaram		 source 8
PharmaSUG 2016 Simulation of Data using the SAS System, Tools for Learning and Experimentation Kevin R. Viel,
Bevan K. Youse		 source 11
SGF 2016 A SAS Macro for Geographically Weighted Negative Binomial Regression Alan Ricardo da Silva,
Thais Rodrigues		 source
zip		 20
SGF 2016 Analyzing Non-Normal Binomial and Categorical Response Variables under Varying Data Conditions Niloofar Ramezani source 16
SGF 2016 Analyzing the Hospital Episode Statistics Data Set: How Much Does SAS Help? Violeta Balinskaite source 9
SGF 2016 Equivalence Tests Fei Wang,
John Amrhein		 source 9
SGF 2016 Fitting Your Favorite Mixed Models with PROC MCMC Gordon Brown,
Fang K. Chen,
Maura E. Stokes		 source 27
SGF 2016 How Do My Neighbors Affect Me? SAS/ETS Methods for Spatial Econometric Modeling Guohui Wu,
Jan Chvosta		 source 13
SGF 2016 PROC GLIMMIX as a Teaching and Planning Tool for Experiment Design Walter W. Stroup source
zip		 19
SGF 2016 Statistical Model Building for Large, Complex Data: Five New Directions in SAS/STAT Software Bob Rodriguez source 23
SGF 2016 Tips and Strategies for Mixed Modeling with SAS/STAT Procedures Phil Gibbs source 21
MWSUG 2015 SAS Software as an Essential Tool in Statistical Consulting and Research Erika Larsen,
Timothy E. O'Brien		 13
PHUSE EU 2015 How to Reduce Bias in the Estimates of Count Data Regression Ashwini Joshi,
Sumit Singh		 source
presentation source		 10
SESUG 2015 Confidence Intervals for Binomial Proportion Using SAS: The All You Need to Know and No More... Confidence Intervals,
Jiangtang Hu		 source 10
WUSS 2015 Constructing Confidence Intervals for a Single Binomial Proportion in SAS William Garner source 8
WUSS 2015 SAS/STAT 14.1: Methods for Massive, Missing, or Multifaceted Data Maura E. Stokes source 25
WUSS 2015 Yes, PROC FREQ does that! AnnMaria De Mars source 15
PharmaSUG 2015 Confidence Intervals Are a Programmer's Friend Xinxin Guo,
Zhaohui Su		 source 8
PharmaSUG 2015 Medication Adherence in Cardiovascular Disease: Generalized Estimating Equations in SAS Erica Goodrich,
Daniel Sturgeon		 source 8
SGF 2015 A Model Family for Hierarchical Data with Combined Normal and Conjugate Random Effects [presentation] Geert Molenberghs source 54
SGF 2015 An Application of the Cox Proportional Hazards Model to the Construction of Objective Vintages for Credit in Financial Institutions, Using PROC PHREG Iván Darío Atehortua Rojas source
zip		 8
SGF 2015 Count Series Forecasting Michael J. Leonard source 14
SGF 2015 Double Generalized Linear Models Using SAS: The %DOUBLEGLM Macro Paulo Silva,
Alan Ricardo da Silva		 source
zip		 16
SGF 2015 Equivalence and Noninferiority Testing Using SAS/STAT Software John M. Castelloe,
Donna Watts		 source 23
SGF 2015 Forest Plotting Analysis Macro %FORESTPLOT Jeffrey P. Meyers,
Qian Shi		 source 18
SGF 2015 Introducing the HPGENSELECT Procedure: Model Selection for Generalized Linear Models and More Gordon Johnston,
Bob Rodriguez		 source 18
SGF 2015 Jeffreys Interval for One-Sample Proportion with SAS/STAT Software Wu Gong source 7
SGF 2015 Risk-Adjusting Provider Performance Utilization Metrics Stephanie Poley source 9
SGF 2015 SAS/STAT 14.1: Methods for Massive, Missing, or Multifaceted Data Maura E. Stokes,
Bob Rodriguez		 source 25
SGF 2015 When Two Are Better Than One: Fitting Two-Part Models Using SAS Laura Kapitula source 9
SESUG 2014 Analysis of Zero Inflated Longitudinal Data Using Proc NLMIXED Delia C Voronca,
Leonard E Egede,
Mulugeta Gebregziabher,
Ralph H. Johnson		 source 18
SESUG 2014 Exploring the Use of Negative Binomial Regression Modeling for Pediatric Peripheral Intravenous Catheterization Jennifer Mann,
Jason Brinkley,
Pamela Larson		 source 7
SESUG 2014 Penalizing Your Models: An Overview of the Generalized Regression Platform Michael Crotty,
Clay Barker		 source 8
PHUSE EU 2014 Biomarker as Essential Part of Clinical Development Renuka Chinthapally source
presentation source		 7
PharmaSUG CN 2014 Calculation of Confidence Intervals for Odds Ratio and Binomial Ratio Using StatXact PROCs Halimu Haridona 7
PharmaSUG 2014 Attain 100% Confidence in Your 95% Confidence Interval Indu Nair,
Binal Patel		 source 9
PharmaSUG 2014 Using SAS to Calculate and Compare Adjusted Relative Risks, Odds Ratios, and Hazard Ratios Besa Smith,
Tyler C. Smith		 source 23
SGF 2014 A SAS Macro for Complex Sample Data Analysis Using Generalized Linear Models Paulo Henrique Dourado da Silva,
Alan Ricardo da Silva		 source 19
SGF 2014 Analysis of Data with Overdispersion Using SAS [presentation] Jorge Morel source 67
SGF 2014 Got Randomness? SAS for Mixed and Generalized Linear Mixed Models David A. Dickey source 12
SGF 2014 Healthcare Services Data Distribution, Transformation, and Model Fitting Dawit Mulugeta,
Jason Greenfield,
Tison Bolen,
Lisa Conley		 source 22
SGF 2014 Reducing Medical Costs Using a System Based on SAS for Provider and Facility Efficiency Scoring Stephanie Poley source 6
SGF 2014 Simulating Portfolio Losses from Adverse Events: Applications to the Insurance and Finance Industries Mahesh V. Joshi,
Jan Chvosta		 source
zip		 20
WUSS 2013 Proper Estimation of Relative Risk Using PROC GENMOD in Population Studies Kechen Zhao source 14
WUSS 2013 User-Specified Likelihood Expressions Using NLMIXED and the GENERAL Statement Melissa McTernan,
Shelley A. Blozis		 source 4
SESUG 2013 Comparisons of SAS Mixed and Fixed Effects Modeling for Observed over Expected Count Outcomes in the Presence of Hierarchical or Clustered Data Rachel E. Patzer source 9
SESUG 2013 Finding the Gold in Your Data: An Overview of Data Mining David A. Dickey source 16
SESUG 2013 Fit Discrete Distributions via SAS Macro Fit Discrete Distributions source 5
SESUG 2013 PROC FORMAT in DATA Step mathematics Elizabeth Schreiber source 5
PHUSE EU 2013 Bayesian Statistics: Concept and Bayesian Capabilities in SAS Mark Janssens source
presentation source		 15
PHUSE EU 2013 Computation of Cls for Binomial Proportions in SAS and its Practical Difficulties Jose Abraham source
presentation source		 8
PHUSE EU 2013 Using PROC GENMOD to Analyses Ratio to Placebo in Change of Dactylitis Imgard Hollweck source
presentation source		 9
MWSUG 2013 Finding the Gold in Your Data: An Overview of Data Mining David A. Dickey 16
MWSUG 2013 Ideas and Examples in Generalized Linear Mixed Models David A. Dickey 12
NESUG 2013 How to Handle Binomial Proportion with Zero Frequency Tulin Shekar 11
PharmaSUG 2013 Combining Analysis Results from Multiply Imputed Categorical Data Bohdana Ratitch,
Ilya Lipkovich,
Michael O'Kelly		 source 19
SGF 2013 Demand Forecasting Using a Growth Model and Negative Binomial Regression Framework Cally Ong Yeru,
Michelle Cheong,
Murphy Choy		 source 17
SGF 2013 Finding the Gold in Your Data: An Overview of Data Mining David A. Dickey source 16
SGF 2013 Markov Chains and Zeros in My Data: Bayesian Approaches in SAS That Address Zero Inflation Matthew Russell source 9
SGF 2013 Models for Ordinal Response Data Robin High source 16
SGF 2013 Using PROC GENMOD to Investigate Drug Interactions: Beta Blockers and Beta Agonists and Their Effect on Hospital Admissions Hui Fen Tan,
Raymond Gregory,
Ronald B. Low,
Shunsuke Ito,
Vann Dunn		 source 10
NESUG 2012 Generalized Additive Models in Marketing Mix Modeling Revisited Patralekha Bhattacharya 9
NESUG 2012 Introducing the FMM Procedure for Finite Mixture Models Maura E. Stokes 22
SESUG 2012 Sample Size Determination for a Nonparametric Upper Tolerance Limit for any Order Statistic Dennis J. Beal source 8
SESUG 2012 Tips and Strategies for Mixed Modeling with SAS/STAT Procedures Kathleen Kiernan,
Jill Tao,
Phil Gibbs		 source 18
MWSUG 2012 ROC Analysis for the Evaluation of Ethyl Glucuronide (EtG) as a Long-term Alcohol Biomarker in Hair and Fingernails: Evidence from a Large College Drinking Study Daniel Fuhrmann,
Michael Fendrich,
Lisa Berger,
Charles Plate,
Doug Lewis,
Joseph Jones		 10
MWSUG 2012 Tips and Strategies for Mixed Modeling with SAS/STAT Procedures Kathleen Kiernan,
Jill Tao,
Phil Gibbs		 18
WUSS 2012 Power Analysis: What is Available and What You Need to Know Gerry Hobbs source 11
WUSS 2012 Up To Speed With Categorical Data Analysis Maura E. Stokes source 25
WUSS 2012 Using SAS to calculate incidence and prevalence rates in a dynamic population Li-Hao Chu,
Fagen Xie		 source 8
PharmaSUG 2012 7 Steps to Progression Free Survival Insights Using SAS Karen Walker source 12
PharmaSUG 2012 Automated forward selection for Generalized Linear Models with Categorical and Numerical Variables using PROC GENMOD Manuel Sandoval source 5
PharmaSUG 2012 Estimating Risk in the Presence of Unreported Zeros in the Data Brandon Fleming source 7
SGF 2012 A Simple Way to Program Power Calculations Robert Lew,
Hongsheng Wu		 source 16
SGF 2012 Beyond Binary Outcomes: PROC LOGISTIC to Model Ordinal and Nominal Dependent Variables Eric P. Elkin source 8
SGF 2012 Effect Modification, Confounding,Hazard Ratio, Distribution Analysis, and Probability of Non-normal Data for Head Neck Cancer Manojkumar B Agravat source 40
SGF 2012 Handling Missing Data by Maximum Likelihood Paul D. Allison source 21
SGF 2012 Including the Salesperson Effect in Purchasing Behavior Models Using PROC GLIMMIX Philippe Baecke,
Dirk Van den Poel		 source 11
SGF 2012 Introducing the FMM Procedure for Finite Mixture Models David Kessler,
Allen McDowell		 source 22
SGF 2012 Tips and Strategies for Mixed Modeling with SAS/STAT Procedures Kathleen Kiernan,
Jill Tao,
Phil Gibbs		 source 18
SCSUG 2011 Statistical comparison of relative proportions of bacterial genetic sequences Jose F Garcia-Mazcorro source 19
SESUG 2011 On Deck: SAS/STAT 9.3 Maura E. Stokes,
Fang K. Chen		 source 20
WUSS 2011 Boost your confidence in a 2x2 standard table Iuliana Barbalau source 8
WUSS 2011 On Deck: SAS/STAT 9.3 Maura E. Stokes source 20
WUSS 2011 Power Analysis: What is Available and What You Need to Know Gerry Hobbs source 11
WUSS 2011 Up To Speed With Categorical Data Analysis Maura E. Stokes source 25
PHUSE EU 2011 Bayesian hypothesis testing for proportions Antonio Nieto,
Javier Gómez		 source
presentation source		 6
MWSUG 2011 On Deck: SAS/STAT 9.3 Maura E. Stokes,
Fang K. Chen,
Ying So		 20
NESUG 2011 A Comparison of PDLREG and GAM Procedures in Measuring Dynamic Effects Patralekha Bhattacharya 11
NESUG 2011 On Deck: SAS/STAT 9.3 Maura E. Stokes 20
PharmaSUG 2011 Evaluating Safety Signals in Clinical Trials: the Dirichlet-NBD Model Implementation with SAS Yuqin Li,
Xiaohai Wan		 source 7
PharmaSUG 2011 FAQ: Issues with Efficacy Analysis of Clinical Trial Data Using SAS Sandeep Sawant,
Nehan Mohan		 source 5
SGF 2011 Bivariate Count Data Regression Models: A SAS Macro Program Nan-Ting Chou,
David Steenhard		 source 10
SGF 2011 Exact Confidence Intervals for Risk-Adjusted Rates Versus Trouble in River City Ted Clay source 11
SGF 2011 Living with Generalized Linear Mixed Models Walter W. Stroup source 18
SGF 2011 On Deck: SAS/STAT 9.3 Maura E. Stokes,
Robert N. Rodriguez,
Funda Güneş		 source 20
SGF 2011 Ratemaking Using SAS Enterprise Miner: An Application Study Billie Anderson source 20
SGF 2011 Repeated Measures Analysis of Correlated Data with Multiple Responses Using SAS Anbuchelvi Jeyabslasingham,
Anpalaki J. Ragavan		 source 10
SGF 2011 Up To Speed With Categorical Data Analysis Gary G. Koch,
Maura E. Stokes		 source 25
SGF 2011 Using SAS Procedures FREQ, GENMOD, LOGISTIC, and PHREG to Estimate Adjusted Relative Risks: A Case Study Jiming Fang source 11
NESUG 2010 An Animated Guide: An introduction to Poisson Regression Russell M. Lavery 17
NESUG 2010 Binomial Reliability Using DATA Step Calculations Elizabeth A. Schreiber 4
NESUG 2010 The Next Generation: SAS/STAT 9.22 Maura E. Stokes,
Robert N. Rodriguez,
Robert Cohen		 20
WUSS 2010 The Next Generation: SAS/STAT 9.22 Robert N. Rodriguez source 20
MWSUG 2010 Adequacy and Information Values: Two Tools for Ranking Predictors in Generalized Linear Models Douglas Thompson 21
MWSUG 2010 Ideas and Examples in Generalized Linear Mixed Models David A. Dickey 12
MWSUG 2010 Novel Use of SAS Software in Industrial and Biomedical Consulting, Research, and Teaching Timothy E. O'Brien 13
MWSUG 2010 The Next Generation: SAS/STAT 9.22 Maura E. Stokes 20
SESUG 2010 The Next Generation: SAS/STAT 9.22 Maura E. Stokes,
Bob Rodriguez,
Robert A. Cohen		 source 20
SGF 2010 Ideas and Examples in Generalized Linear Mixed Models David A. Dickey source 12
SGF 2010 The Next Generation: SAS/STAT 9.22 Maura E. Stokes,
Robert N. Rodriguez		 source 20
MWSUG 2009 A Class of Predictive Models for Multi-Level Risks Wensui Liu,
Chuck Vu,
Sandeep Kharidhi		 13
WUSS 2009 Group Confidence Limit Plots Using PROC GPLOT and PROC SGPLOT Robert A. Rutledge source 10
PharmaSUG 2009 Are you computing Confidence Interval for binomial proportion using PROC FREQ? Be Careful!! Sandeep Sawant 6
PharmaSUG 2009 Confidence Intervals for the Binomial Proportion with Zero Frequency Xiaomin He,
Shwu-Jen Wu		 6
PharmaSUG 2009 ROC analysis for the evaluation of continuous biomarkers: Existing tools and new features in SAS 9.2 Sanghyuk Shin 15
PharmaSUG 2009 Using SAS/IML to Generate Weighted Chi-Square Statistics Daniel DiPrimeo,
Bruce Johnston,
Lisa Price,
Junming Yang		 8
SGF 2009 A Class of Predictive Models for Multi-Level Risks Wensui Liu,
Chuck Vu,
Sandeep Kharidhi		 source 13
SGF 2009 A Flexible Count Data Regression Model Using SAS PROC NLMIXED Nan-Ting Chou,
David Steenhard		 source 14
SGF 2009 Bayesian Modeling Using the MCMC Procedure Fang K. Chen source 22
SGF 2009 Comparison of Features and Applications of Four Linear Models Procedures Larry W. Douglass source 19
SESUG 2008 Count Regression Models in SAS David Steenhard,
Nan-Ting Chou		 source 12
SESUG 2008 Lithium Battery Analysis: Probability of Failure Assessment Using Logistic Regression Travis A. Moebes source 9
PHUSE EU 2008 Evaluation of Diagnostic Agents: a SAS Macro for Sample Size Estimation Using Exact Methods Stefano Vezzoli source 8
MWSUG 2008 Confidence Interval Calculation for Binomial Proportions Keith Dunnigan 12
MWSUG 2008 Using Direct Standardization SAS Macro for a Valid Comparison in Observational Studies Daojun Mo,
Xia Li,
Alan Zimmermann		 11
NESUG 2008 Fitting Generalized Additive Models with the GAM Procedure in SAS 9.2 Weijie Cai 14
NESUG 2008 Using PROC DOCUMENT To Modify PDF Bookmarks Generated by PROC FREQ Suzanne M. Dorinski 10
SGF 2008 Applying SAS Mixed-Model Procedures to Educational-Assessment Data Brian Patterson source 8
SGF 2008 Count Data Models in SAS Wensui Liu,
Jimmy Cela		 source 12
SGF 2008 Fitting Generalized Additive Models with the GAM Procedure in SAS 9.2 Weijie Cai source 14
SGF 2008 Lithium Battery Analysis: Probability of Failure Assessment Using Logistic Regression Travis A. Moebes source 9
SGF 2008 Modeling Zero-Inflated Count Data with Underdispersion and Overdispersion Adrienne Tin source 11
SGF 2008 Pricing of Options Using Hybrid Artificial Neural Networks Anant Saxena source 25
SGF 2008 Updates to SAS Power and Sample Size Software in SAS 9.2 Wayne E. Watson source 10
SGF 2008 Zero-Inflated Poisson and Zero-Inflated Negative Binomial Models Using the COUNTREG Procedure Donald Erdman,
Arthur V. Sinko		 source 11
NESUG 2007 Butting Heads on Matched Cohort Analysis Using SAS Software Melvin T. Alexander 12
NESUG 2007 Nonlinear Programming for Maximum Likelihood Estimation Robert J. Gallop 12
NESUG 2007 Summarizing the Power of Your Predictive Model with Receiver Operating Characteristic Curves Mithat Gonen 18
NESUG 2007 Using PROC GENMOD to Model Adverse Event Counts in a Healthcare Setting John Ulicny,
Thomas Klumpp		 13
WUSS 2007 Statistical Inference Illustrated Richard R. Allen source 19
PNWSUG 2007 Multiple comparisons on 2xc proportions John Horne 12
PharmaSUG 2007 Cochran-Armitage Trend Test Using SAS Hui Liu 11
SGF 2007 A SAS Macro for Automating the Change-In-Estimate Strategy for Assessing Confounding Julius Ta,
Myduc L. Atashili		 source 10
SGF 2007 Growing Up Fast: SAS 9.2 Enhancements to the GLIMMIX Procedure Oliver Schabenberger source 20
PHUSE EU 2006 Having Confidence in non-parametric data John Salter source 8
SESUG 2006 Combining PROC GENMOD Models with Multinomial Outcomes Using PROC MIANALYZE Marie Gantz source 7
SESUG 2006 Creating RTF Tables with Univariate Analyses of Multiply Imputed Data Marie Gantz source 14
WUSS 2006 PROC GENMOD with GEE to Analyze Correlated Outcomes Data Using SAS Tyler C. Smith,
Besa Smith		 source 14
WUSS 2006 Real-Time Sales Volumes Projection with SAS - A Challenge in Implementing a Data-Based Solution in the Automobile Industry Keiko I. Powers source 8
NESUG 2006 Receiver Operating Characteristic (ROC) Curves Mithat Gonen 18
NESUG 2006 Using PROC GENMOD to Model Adverse Event Counts in a Healthcare Setting John Ulicny,
Thomas Klumpp		 13
PharmaSUG 2006 Generating Half-normal Plot for Zero-inflated Binomial Regression Zhao Yang,
Xuezheng Sun		 12
SUGI 2006 Assessing Within- and Between-Individual Effects Using Correlated Data from an HIV Clinical Trial Marla J. Husnik,
Grant Colfax,
Eugene Huang		 source 10
SUGI 2006 Fixed Effects Regression Methods in SAS Paul D. Allison source 20
SUGI 2006 FREQ n' MEANS Marge Scerbo,
Michael S. Lajiness		 source 19
SUGI 2006 Receiver Operating Characteristic (ROC) Curves Mithat Gonen source 18
SUGI 2006 The Estimation of Sensitivity and Specificity of Clustered Binary Data William F. McCarthy,
Nan Guo		 source 10
PNWSUG 2005 Assessing Within- and Between-Subject Effects with Correlated Clinical Data Marla J. Husnik,
Eugene Huang,
Grant Colfax		 10
MWSUG 2005 A Macro For The Calculation Of Age, Gender And Race Adjusted Incidence And Mortality Rates Padmini Sekar 12
WUSS 2005 A Programmer's Guide to Statistical Procedures Jim Edgington source 4
WUSS 2005 Analysis of Group-Randomized Designs: A clinic-based breast cancer rescreening example Jesse Albert Canchola,
Regina Otero-Sabogal		 source 9
WUSS 2005 Introducing the GLIMMIX Procedure for Generalized Linear Mixed Models Oliver Schabenberger source 20
NESUG 2005 Freq n' Means Marge Scerbo,
Michael S. Lajiness		 19
NESUG 2005 Introducing the GLIMMIX Procedure for Generalized Linear Mixed Models Oliver Schabenberger 20
PharmaSUG 2005 Assessing Within- and Between-Subject Effects with Correlated Clinical Data Marla J. Husnik,
Eugene Huang,
Grant Colfax		 10
SUGI 2005 Estimation of Type III Error and Power for Directional Two-Tailed Tests Using PROC POWER Cam-Loi Huynh source 10
SUGI 2005 Introducing the GLIMMIX Procedure for Generalized Linear Mixed Models Oliver Schabenberger source 20
SUGI 2005 Power Simulation for Categorical Data Using the RANTBL Function Joel A. Dubin,
Theodore R. Holford,
Peter H. Van Ness		 source 12
SUGI 2005 PROC FREQ and PROC MEANS: To Stat or Not to Stat Marge Scerbo,
Michael S. Lajiness		 source 17
SUGI 2005 Teaching Data Mining in a University Environment David A. Dickey source 11
SCSUG 2004 Ranking Efficiency, Properness with SAS Probability Functions and Procedures Dagan Zhang 8
SESUG 2004 A Simulation Study to Evaluate ANOVA and GEE for Comparing Correlated Proportions with Missing Values Mark S. Litaker source 6
WUSS 2004 Beyond Binary Outcomes: PROC LOGISTIC to Model Ordinal and Nominal Dependent Variables Eric P. Elkin source 8
WUSS 2004 PROC GENMOD for Analysis of Correlated Outcome Data Using the LOGIT Link Function Tyler C. Smith,
Besa Smith,
William Honner,
Ming Ji		 source 14
SUGI 2004 Some Statistical Strategies for Analyzing Confirmatory Studies Involving One or More Occurrences of Primary Events Gary G. Koch,
Maura E. Stokes		 source 21
WUSS 2003 Presenting Logistic Regression Models to Non-Statisticians: Adjusted Probabilities and Adjusted Risk Ratios David J. Pasta,
Miriam G. Cisternas		 source 4
MWSUG 2003 Parameter Estimation of a Negative Binomial for the By-product of the Gringard Reaction Ling Huang,
Paul W. Johnson		 4
NESUG 2003 A SAS Program for Estimating Incidence Density for Cohort Studies with Multiple Follow-ups Jinbing Zhang,
Xiaofang Yu		 5
NESUG 2003 Backwards Manual Selection (%bms): A Macro for Selecting Logistic Regression Models to Address Epidemiological Research Questions Janice Hegewald,
Anette Pfahlberg,
Wolfgang Uter		 5
NESUG 2003 Drawing Multiple Random Samples with Replacement Charles A. DePascale 2
SEUGI 2003 Using the SAS System for Teaching and Research - A Short Review of Co-operations between Statisticians and Medical Students [presentation] Barbara G. Schneider source 59
PharmaSUG 2003 Confidence Intervals in Analysis and Reporting of Clinical Trials Guangbin Peng 8
SUGI 2003 Estimation of Prevalence Ratios When PROC GENMOD Does Not Converge James A. Deddens,
Martin R. Petersen,
Xiudong Lei		 source 6
SUGI 2003 Using the SAS System to Construct and Operate Control Charts with Randomized Control Limits Peter S. Wludyka source 7
SESUG 2002 Using SAS to Control Multistream Binomial Processes with a Chi-Squared Control Chart Peter S. Wludyka source 5
WUSS 2002 Doing More with Proce FREQ Using Options and ODS Richard Severino source 13
NESUG 2001 A Comparison of Binomial Proportion Interval Estimation Methods John Ulicny 7
WUSS 2001 A Macro for Calculating and Displaying Smoking Prevalence and Confidence Intervals Brett Holbrook source 3
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
SESUG 2001 P713 Using SAS To Control Multistream Binomial Processes Peter S. Wludyka,
Sheri Jacobs		 source 8
SESUG 2001 Understanding and Using Functions Frank C. DiIorio source 8
SCSUG 2001 Understanding and Using Functions Frank C. DiIorio 8
SCSUG 2001 Using SAS to Control MultiStream Binomial Processes Peter S. Wludyka,
Sheri Jacobs		 8
SEUGI 2001 Teaching statistics and the SAS System Barbara G. Schneider source 10
PharmaSUG 2001 Fitting Generalized Additive Models with the GAM Procedure Dong Xiang 8
SUGI 2001 A Reader's Guide toVisualizing Categorical Data Michael Friendly source 8
SUGI 2001 Analysis of Count Data Using SAS Alexander Pedan source 6
SUGI 2001 Fitting Generalized Additive Models with the GAM Procedure Dong Xiang source 8
SUGI 2001 How the SAS System Can Be Used for Teaching Statistics Barbara G. Schneider source 4
NESUG 2000 Applying Survival Analysis Techniques to Loan Terminations for HUD's Reverse Mortgage Insurance Program - HECM Ming H. Chow 8
NESUG 2000 Confirmatory and Exploratory Data Analyses Using PROC GENMOD: Factors Associated with Red Light Running Crashes Li wan Chen 7
NESUG 2000 Think Outside the Box: Analysis of Categorical Data Margaret Ann Goetz 5
WUSS 2000 PROC FREQ: It's More Than Counts Richard Severino source 10
SEUGI 2000 Credit Risk Measurement for a Bank Loans Portfolio Emiliano Laruccia,
Valter Lazzari		 source 11
SEUGI 2000 SAS Software for the Analysis of Epidemiologic Data [presentation] Hans-Peter Altenburg source 39
SEUGI 2000 Skaen but not stirred - Why I like NLMIXED [presentation] Tim Auton source 38
PharmaSUG 2000 Meta-Analysis with Linear and Nonlinear Multilevel Models Using PROC MIXED and PROC NLMIXED Eugene Komaroff,
Russell D. Wolfinger		 4
SUGI 2000 PROC FREQ: It's More Than Counts Richard Severino source 10
SUGI 2000 Qualitative and Limited Dependent Variable Models using the New QLIM Procedure Minbo Kim source 7
SUGI 2000 Visualizing Categorical Data: Data, Stories, and Pictures Michael Friendly source 9
SCSUG 1999 An Introduction to Gibbs Sampling Scott Burk 9
SESUG 1999 A SAS Program to Calculate and Plot Widths of (1-α)100% Confidence Intervals for Binomial Proportions Maribeth H. Johnson,
Mark S. Litaker		 source 2
SESUG 1999 Forecasting Army Officer Attrition with Logistic Regression Using The SAS System Douglas L. McAllaster source 10
NESUG 1999 Fitting Nonlinear Mixed Models with the New NLMIXED Procedure Russell D. Wolfinger 10
SUGI 1999 Fitting Nonlinear Mixed Models with the New NLMIXED Procedure Russell D. Wolfinger source 10
MWSUG 1998 A Tour of UnifyPow: A SAS Module/Macro for Sample-Size Analysis Ralph G. O'Brien 11
WUSS 1998 Data Warehouses and Bayesian Analysis - A Match Made by SAS Ram Gopalan source 6
SUGI 1998 A SAS Macro to Calculate Exact Confidence Intervals for the Difference of Two Proportions Paul R. Coe source 6
SUGI 1998 A Tour of UnifyPow: A SAS Module/Macro for Sample-Size Analysis Ralph G. O'Brien source 10
SUGI 1998 Skaff and Jeff A. Sloan Design and Analysis of Equivalence Clinical T rials V ia the SAS System Pamela J. Atherton source 7
SUGI 1998 Statistical Process Monitoring of Correlated Binary and Count Data Using Mixture Distributions Jose G. Ramirez,
Brenda S. Cantell,
Randall S. Collica		 source 7
SCSUG 1997 Reliability Data Analysis in the SAS System Gordon Johnston 10
PNWSUG 1997 Qualitative Choice Models Donald M. Perry 2
WUSS 1997 Reliability Data Analysis in the SAS System Donna O. Fulenwider,
Gordon Johnson		 source 10
NESUG 1997 Using Logistic Regression to Test for Interaction in the Presence of Zero Cells Lisa Suchower 10
MWSUG 1997 Reliability Data Analysis in the SAS System Gordon Johnston 10
MWSUG 1997 Using SAS/STAT to Analyze Correlated Data Marlene Goormastic 7
SESUG 1997 Analysis of Repeated Measures and Longitudinal Data Jane Pendergast 8
SUGI 1997 An Experiment Analysis System for Fixed and Random Effects in OverDispersed Binomial Responses in Semiconductor Manufacturing Jose G. Ramirez,
Randall S. Collica		 source 6
SUGI 1997 UnifyPow: A SAS Macro for Sample-Size Analysis Ralph G. O'Brien source 6
SESUG 1996 A SAS Program to Calculate and Plot Widths of (1-α)100% Confidence Intervals for Binomial Proportions Maribeth H. Johnson,
Mark S. Litaker		 2
SESUG 1996 Simulation of Data for Monte Carlo Studies of Prevalence Estimation in Two-Phase Cross-Sectional Epidemiologic Studies Mark S. Litaker 4
NESUG 1996 Using the SAS System to Perform McNemar's Test and Calculate the Kappa Statistic for Matched Pairs of Data Lisa Suchower,
Margaret Copenhaver		 8
MWSUG 1996 Applying Generalized Linear Models to Discrete Response Data Using the SAS System Maura E. Stokes 2
SEUGI 1996 Backtesting or backestimating: an overview Gerhard Stahl source 7
SEUGI 1996 Motor and Household Insurance: Pricing to Maximise Profit in a Competitive Market Tom Wright source 10
SUGI 1996 Repeated Measures Analysis with Discrete Data Using the SAS System Gordon Johnston source 5
MWSUG 1995 Making Inference for Reliability Indices based on Beta Binomial Model with SAS Software Jianli Li 4
MWSUG 1995 SAS Macros for Exact Confidence Limits Richard L. Berg 6
NESUG 1995 When Chi-Square Does Not Hold: How to Analyze Tables With Low Cell Frequencies With SAS Lothar Tremmel 9
WUSS 1995 Implementation of a Simple Method for the Analysis of Over-Dispersed Counts and Proportions Jennifer Lee,
Chul W. Ahn		 source 3
SUGI 1995 A Comparative Evaluation of Selected Statistical Software for Computing Various Categorical Analyses Nancy McDermott,
Cynthia White		 source 6
SUGI 1995 Bartlett Correction of Binomial Regression Analyses of Small Samples Lawrence Moulton,
Roy St. Laurent,
Lisa Weissfeld		 source 5
SUGI 1995 Batch Processing in SAS/INSIGHT Software Heman Robinson source 8
SCSUG 1994 Two Macros for Calculating Often Used Statistics of Symmetry and Agreement in the Biopharmaceutical Industry Jeff Heckathorn,
Mark F. Munsell		 12
NESUG 1994 A SAS Macro for Exact Power of Chi-Square Tests of Equality of Two Proportions Carl E. Pierchala 10
SEUGI 1994 Cross Validation of Nearest-neighbour Discriminant Analysis Allan White source 15
SEUGI 1994 Resampling Using SAS/IML Software Some Medical Applications Gina Joubert source 8
SUGI 1994 A Macro-Based Approach for Calculating Binomial Probabilities Daniel R. Bretheim source 6
SUGI 1994 Log Negative Binomial Regression Using the GENMOD Procedure SAS/STAT Software Joseph M. Hilbe source 6
SUGI 1994 Nonstandard Uses of PROC MULTTEST: Permutational Peto Tests; Permutational and Unconditional T and Binomial Tests Peter H. Westfall,
Keith A. Soper		 source 4
SUGI 1994 Programming the NUN Procedure Using the Negative Binomial Yield Model for ASIC Semiconductors Jon A. Patrick source 4
WUSS 1993 A SAS Program for Sample Size Determination for Equivalence Trials Akiko Tomita,
Chul W. Ahn,
Joyce C. Niland		 source 6
WUSS 1993 Using SAS Software to Implement a Simple Method for the Analysis of Clustered Binary Data Tamara Odom-Maryon,
Chul W. Ahn		 source 5
SEUGI 1993 Exploratory Data Analysis Using SAS Software Gerhard Held source 11
SEUGI 1993 Support of Statistical Consulting Using SAS Software Hans-Peter Altenburg source 11
SUGI 1993 An Application of SAS Software in Auditing and Finance: Monetary Unit Sampling Pankaj Patel,
Laura G. Bacon		 source 6
SUGI 1993 Exploratory Data Analysis Using SAS Software Greg J. Weier,
Randall D. Tobias		 source 11
SUGI 1993 SAS Software to Fit the Generalized Linear Model Gordon Johnston source 8
SEUGI 1992 SAS/INSIGHT Software: Introduction and New Features Gerhard Held source 7
SEUGI 1992 Using SAS Macros and PROC IML to Create Special Designs for Use in Generalised Linear Models John Hendrickx source 22
SUGI 1992 Proportional Hazards Analysis of Left-truncated Survival Data Dennis Heisey source 6
SCSUG 1991 Confidence Intervals for Bionomial Distributions Using SAS Graphics and PROBBNML Alan Davis 7
SEUGI 1991 A Graphical Demonstration of Statistical Concepts Marlies Lacante source 13
SUGI 1991 A Procedure for Deciding Which Treatments to Accept in a Screening Study Involving Pseudo-Bernoulli Data Ralph A. DeMasi,
Dana Quade		 source 7
SUGI 1991 Evaluating the Probability Distribution of the Sum of Independent Finite Integer-Valued Random Variables Daniel R. Jeske,
Thomas M. Willis,
Ying C. So		 source 6
SUGI 1991 Exact Confidence Intervals for Estimating Proportions When Sampling from a Finite Population How J. Tsao,
Steven M. LaLonde		 source 5
MWSUG 1990 The Pair Chart Macro: A quick Graphical Representation of the Two-Sample Problem Michael Riggs 10
SUGI 1990 Determining Sample Sizes Needed to Achieve the Specified Confidence Levels - Binomial Distribution Approach Shi-Tao Yeh source 4
SUGI 1990 The GLIM Procedure: An Interface to the SAS System P. M. Grambsch,
Jon L. Kosanke,
Terry M. Therneau,
D. J. Schaid,
R. Zinsmeister,
H.S. Wieand,
Kenneth P. Offord,
J. J. LarsonKeller		 source 5
SEUGI 1989 Realization Of Approximative And Exact Nonparametric Statistics In SAS/IML Software Siegfried Freytag source 10
SUGI 1989 A Procedure for the Analysis of Multivariate Binomial Data with Adjustments for Multiplicity Youling Lin,
Peter H. Westfall,
S. Stanley Young		 source 8
SUGI 1989 Analysis of the Properties of Two Binomial Random Number Generators J. Paul Costiloe,
Andrew J. Cucchiara,
Susan J. Kenny		 source 3
SUGI 1989 Field Reliability Assessment Using the Proportional Hazards Model Stephen Freitas,
Raymond V. Spring		 source 5
SUGI 1989 P-Value Adjustments for Multiple Tests in Multivariate Binomial Models Peter H. Westfall,
S. Stanley Young		 source 4
SUGI 1989 Processing and Analyzing Consumer Panel Data Charles F. Hofacker source 4
SUGI 1988 Spatial Pattern Analysis John M. LaBore source 6
SUGI 1988 Type I Error Rate for Small Sample Sizes Using Various Options of the CATMOD Procedure J. Paul Costiloe,
Andrew J. Cucchiara,
Susan J. Kenny		 source 4
SUGI 1987 Effect of Iteratively Reweighted Least Squares (IRLS) on Teaching A Course in Quantal/Categorical Response Rita C. Berg,
James E. Dunn		 source 6
SUGI 1987 Full-screen Menu-driven Sample Size Programs Using SAS/AF Software J.A. Bebar,
Phil Cirulli,
L. A. Johnson		 source 5
SUGI 1987 Generating Sample Sizes for Hypergeometric Sampling. Plans Using SAS Software Melvin T. Alexander source 5
SEUGI 1986 Generalized Linear Models in SAS Using PROC GLM James Roger source 10
SUGI 1986 A SAS Macro Which Computes Upper Confidence Limits of the Number of Defective Units in a Lot Melvin T. Alexander source 4
SUGI 1985 A SAS Procedure for Smoothing Generalized Linear Models William J. Raynor Jr. source 6
SUGI 1985 A SAS Routine to Compute Minimum Sample Sizes for Single Attribute Sampling Plans Melvin T. Alexander source 4
SUGI 1985 Implementing IMSL Routines as SAS Functions Michael Conlon source 2
SUGI 1985 MACRO LGTREG for Logistic Regression and Associated Diagnostics Thomas F. Devlin,
Barbara J. Weeks		 source 6
SUGI 1984 SAS Functions Useful for Probability Computations N. D. Prabhakar source 2
SUGI 1983 Accessing Vendor and User-written Subroutines with SAS Richard A. Boro,
Elaine S. Pretz		 source 6
SUGI 1983 PROC DISCRETE-A Procedure for Fitting Discrete Probability Distributions Charles E. Gates,
James P. Geaghan,
George D. Williams		 source 4
SUGI 1983 PROC Paired Bradley J. Dain,
Jon L. Kosanke,
Kenneth P. Offord		 source 2
SUGI 1981 A Comparison of Several Approaches for Calculating LC50s for Binary Responses from Toxicological Experiments Charles M. Bundrick,
Jerry L. Oglesby		 source 8
SUGI 1981 On the Role of Redundant Information in Error Detection Ronald W. Helms source 5

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