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interaction effect

138 papers and 2 presentations; 133 titles.

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Conference × Year × Title × Authors Extras Pages
PHUSE APAC 2026 Working with Biomarker - What Every Programmer Should Know Aboli Katdare source
presentation source		 14
SESUG 2025 Writing ESTIMATE statements to compare continuous scores over time overall and by group Alexis Wardell,
Allison M. Deal		 18
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
SESUG 2024 A Comprehensive Analysis of the Relationship Between Depression, Sleep Deprivation, and Self-Esteem Using Advanced Statistical Methods Muslihat Adejoke Gaffari source 43
WUSS 2023 D-I-D the policy have an impact? Difference-in-difference methods applied to survey data in SAS Melanie Dove source 7
SGF 2020 Analyzing the Factors Impacting Suicidal Behavior in American Youth Ashlesha Sampathi source 7
SGF 2020 Don't Just Survive, Thrive with This Multi-Stratified Cox Proportional Hazards Model Macro Katelyn J. Ware,
Paul Egeler		 source 11
SGF 2020 Time After Time: D-I-D and ITS Models in SAS Margaret Warton source 21
SESUG 2019 Don't Let Complex Survey Data Get the Best of You! SAS Survey PROCs for Categorical Data Analysis Charlotte Baker source 14
SESUG 2019 The Thorn in My Side!! Logistic Regression Continuous Variables that Violate the Assumption of Linearity on the Log-odds (Logit) Scale: How to Identify and What to Do? Janet M. Grubber,
Cynthia J. Coffman		 source 13
MWSUG 2019 Surviving Survival Analysis 101: Making the Likelihood Ratio Test Easier Using a Macro Katelyn Ware,
Rachel Baxter		 13
PharmaSUG 2019 A SAS Macro to Provide Survival Functions along with Cox Regression Model Efficiently Chia-Ling (Ally) Wu source 6
SGF 2019 Don't Let Complex Survey Data Get the Best of You! SAS Survey PROCs for Categorical Data Analysis Charlotte Baker source 16
PHUSE EU 2018 Collinearity in Mixed Models John Hendrickx source
presentation source		 11
WUSS 2018 Oops, I D-I-D It Again! Advanced Difference-in-Differences Models in SAS Margaret Warton,
Melissa Parker		 source 17
SGF 2018 A SAS Macro Implementation of a Test for Co-directional Interactions Julia Sharp,
Patrick Gerard,
Bereket Tesfaldet		 source 16
SGF 2018 Location Matters: Evidence from Spatial Econometric Analysis of Opioid Prescription Rates Jonathan Mccopp source 21
SGF 2018 Using Information Value, Information Gain, and Gain Ratio for Detecting Two-Way Interaction Effect Alec Zhixiao Lin source 19
PharmaSUG 2017 Multinomial Logistic Regression Models With Sas Proc Surveylogistic Marina Komaroff source 7
MWSUG 2016 To be two or not be two, that is a LOGISTIC question Robert G. Downer 10
WUSS 2016 How D-I-D you do that? Basic Difference-in-Differences Models in SAS Margaret Warton,
Melissa Parker,
Andrew Karter		 source 11
PharmaSUG 2016 Mixed Effects Models Yan Wang source 7
SESUG 2015 Introducing Two-Way and Three-Way Interactions into the Cox Proportional Hazards Model Using SAS Seungyoung Hwang,
Johns Hopkins		 source 5
SGF 2015 Sums of Squares: The Basics and a Surprise Sheila Barron,
Michelle Mengeling		 source 8
SGF 2015 The %ic_mixed Macro: A SAS Macro to Produce Sorted Information Criteria (AIC and BIC) List for PROC MIXED for Model Selection Qinlei Huang source 16
SGF 2015 Using SAS to Deliver Web Content Personalization Using Cloud-Based Clickstream Data and On-premises Customer Data Mahesh Subramanian,
Suneel Grover		 source 24
SGF 2015 Using the GLIMMIX and GENMOD Procedures to Analyze Longitudinal Data from a Department of Veterans Affairs Multisite Randomized Controlled Trial Abbas S. Tavakoli,
Marlene Al-Barwani,
Sue Levkoff,
Selina McKinney,
Nikki R. Wooten		 source 11
SESUG 2014 Overview of Analysis of Covariance (ANCOVA) Using GLM in SAS Abbas S. Tavakoli source 10
SGF 2014 A Stepwise Algorithm for Generalized Linear Mixed Models Nagaraj Neerchal,
Jorge Morel,
Xuang Huang,
Alain Moluh		 source 11
PHUSE EU 2013 Lexis Expansion - Age-at-Risk Adjustment for Survival Analysis Lai San Hong,
Sarah Lewington		 source 5
NESUG 2013 Analyzing the Safewalk Program with SAS: Saving Shelter Dogs One Walk at a Time Louise S. Hadden,
Terri Bright		 12
PharmaSUG 2013 Time to Event Analysis in the Pharmaceutical and Medical Device Industries Helen M. Chmiel,
Evan L. Ritzema		 source 8
SGF 2013 Analyzing Partially Confounded Factorial Conjoint Choice Experiments Using SAS/IML Chin Khian Yong,
Song Lin Ng		 source
pdf		 11
SGF 2013 Regression of NASCAR: Looking into Five Years of Jimmie Johnson Alex Herrington,
Liuchun Yang,
Yun Gao		 source 20
NESUG 2012 Analyzing the Safewalk Program with SAS: Saving Shelter Dogs One Walk at a Time Louise S. Hadden,
Terri Bright		 12
NESUG 2012 Using SAS to Test, Probe and Display Interaction Effects in Regression Timothy Gravelle 16
SESUG 2012 Compare MIXED and GLMMIX to Analyze Breast Cancer Longitudinal Study Abbas S. Tavakoli source 5
MWSUG 2012 Methods for Interaction Detection in Predictive Modeling Using SAS Douglas Thompson 13
WUSS 2012 Sample Size Calculation and Power Analysis for Design of Experiments Using Proc Glmpower Chii Dean source 10
SGF 2012 A Generalized Approach to Estimating Sample Sizes Wuchen Zhao,
Arthur X. Li		 source 7
SESUG 2011 Analysis of a Binary Outcome Variable Using the FREQ and LOGISTIC Procedures Arthur X. Li source 18
SESUG 2011 Evaluating Consumer Price Behavior Using JMP Joshua Klick source 6
SESUG 2011 Proc MIXED - Right Options to get Right Output Shilpa C. Edupganti,
Sheetal Nisal		 source 9
SESUG 2011 Tailoring Logistic Regression Model Analyses with the ODDSRATIO Statement in PROC LOGISTIC Taylor Lewis source 8
WUSS 2011 Estimating Disease Prevalence from Clinical Data Using Capture-Recapture Carol Conell source 10
WUSS 2011 Estimating Sample Size through Simulations Wuchen Zhao source 6
PHUSE EU 2011 Estimation of relative potency in a 4-point parallel line assay Stefano Vezzoli source
presentation source		 11
MWSUG 2011 Using JMP Visualizations to Build a Statistical Model George J. Hurley 11
NESUG 2011 Proc Mixed - Right Options to Get the Right Output Shilpa C. Edupganti,
Sheetal Nisal		 10
PharmaSUG 2011 CONTRAST and ESTIMATE Statements Made Easy: The LSMESTIMATE Statement Kathleen Kiernan,
Randy Tobias,
Phil Gibbs,
Jill Tao		 source 19
PharmaSUG 2011 Estimating Sample Size through Simulations Wuchen Zhao,
Arthur X. Li		 source 6
PharmaSUG 2011 FAQ: Issues with Efficacy Analysis of Clinical Trial Data Using SAS Sandeep Sawant,
Nehan Mohan		 source 5
SGF 2011 CONTRAST and ESTIMATE Statements Made Easy: The LSMESTIMATE Statement Kathleen Kiernan,
Randy Tobias,
Phil Gibbs,
Jill Tao		 source 19
SGF 2011 To Hash or Not To Hash! That Is the Question!! When it Comes to SQL!!! Mustaq Ahmad source 12
SGF 2011 Using JMP Visualizations to Build a Statistical Model George J. Hurley source 11
SGF 2011 Visualizing Marginal Effects from Interactions in Generalized Linear Models Xiao Chen,
Brigid Wilson		 source 7
MWSUG 2010 Adequacy and Information Values: Two Tools for Ranking Predictors in Generalized Linear Models Douglas Thompson 21
SESUG 2010 SAS Macros for Estimating the Attributable Benefit of an Optimal Treatment Regime Jason Brinkley source 12
SGF 2010 Custom Designs Using JMP Design of Experiments and SAS PROC OPTEX Mei-Fen Yeh,
Anthony Cece,
Mark A. Presser		 source 9
SESUG 2009 A Logistic Regression Model to Predict Freshmen Enrollments Vijayalakshmi Sampath,
Andrew Flagel		 source 12
SESUG 2009 An Easy and Convenient Method for Constructing Contrasts Robert Vogel source 5
SESUG 2009 Using SAS to Explain Mediator and Moderator Effect for Social Support of Mothers of Mentally Ill Children Abbas S. Tavakoli source 13
MWSUG 2009 Mixed Model Selection George C. J. Fernandez 19
WUSS 2009 Automating the Process of Scoring a Generalized Linear Model Fitted using PROC GENMOD Prakash Gurumurthy source 9
WUSS 2009 Computing Hazard Ratios and Confidence Intervals for a Two-Factor Cox Model with Interaction Terms Marla J. Husnik,
Jing Wang		 source 10
PharmaSUG 2009 Adhoc Analysis of Site By Treatment Interaction Alan Davis 9
PharmaSUG 2009 Computing Hazard Ratios and Confidence Intervals for a Two-Factor Cox Model with Interaction Terms Jing Wang,
Fred Hutchinson Cancer		 10
PharmaSUG 2009 Generating Model Based Subgroup Analysis Using SAS Procedures Tracy Lin,
Jie Huang		 4
PharmaSUG 2009 Illustrative Logistic Regression Examples using PROC LOGISTIC: New Features in SAS/STAT 9.2 Robert G. Downer,
Patrick J. Richardson		 11
SGF 2009 A SAS Macro for Adaptive Regression Modeling George J. Knafl source 9
SGF 2009 Examining Mediator and Moderator Effect Using Rural-Women HIV Study Kirby Jackson,
Linda Moneyham,
Abbas S. Tavakoli		 source 6
SGF 2009 Optimizing the Marketing Mix Patralekha Bhattacharya source 5
WUSS 2008 User-friendly SAS Macro Application for performing all possible mixed model selection - An update George C. J. Fernandez source 19
SESUG 2008 Optimizing the Marketing Mix Patralekha Bhattacharya source 4
SESUG 2008 Parsimony vs. Complexity: A Comparison of Two-Level, Three-Level, and Cross-Classified Models Using Add Health and AHAA Data Bethany A. Bell,
Corina M. Owens,
John M. Ferron,
Jeffrey D. Kromrey		 source 13
NESUG 2008 Optimizations in Marketing Mix Modeling Patralekha Bhattacharya 4
PharmaSUG 2008 The Logic and Logistics of Logistic Regression Lawrence Rasouliyan,
Dave P. Miller		 14
PharmaSUG 2008 TPHREG and GLMSELECT: Using the CLASS statement in SAS 9.1 Laura E. Archer 11
SGF 2008 Horizon Estimation Using SAS Software Gary A. Foster,
Charles Goldsmith		 source 9
WUSS 2007 Time Series Cross Sectional Analysis of Total Nitrogen Concentration in Truckee River, Nevada Using SAS Anpalaki J. Ragavan source 11
PharmaSUG 2007 Effects of Multicollinearity in All Possible Mixed Model Selection George C. J. Fernandez 18
SGF 2007 Growing Up Fast: SAS 9.2 Enhancements to the GLIMMIX Procedure Oliver Schabenberger source 20
SGF 2007 Model Selection in PROC MIXED-A User-Friendly SAS Macro Application George C. J. Fernandez 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
MWSUG 2006 All Possible Model Selection in Proc Mixed - A SAS macro application George C. J. Fernandez 19
PHUSE EU 2006 The Hazards of Modelling Proportional Hazards in SAS Erika Daly,
Farzana Sufi		 source 4
WUSS 2006 Hierarchical Logistic Regression Modeling with SAS GLIMMIX Jian Dai,
Zhongmin Li,
David Rocke		 source 9
WUSS 2006 Model Selection Methods in PROC MIXED George C. J. Fernandez source 19
WUSS 2006 The Logic and Logistics of Logistic Regression Lawrence Rasouliyan,
Dave P. Miller		 source 14
SUGI 2006 AMMI Macros for Multiplicative Interaction Models Eun-Joo Lee,
Dallas E. Johnson		 source 10
SUGI 2006 Investigating Open Source Project Success - A Data Mining Approach to Model Formulation, Testing and Validation Uzma Raja,
Marietta J. Tretter		 source 7
SUGI 2006 Using SAS to Investigate Effect Modification Peter H. Van Ness,
Heather G. Allore		 source 10
MWSUG 2005 Calculation Of Health Disparity Indices Using Data Mining And The SAS Bridge To ESRI Mussie A. Tesfamicael 9
PharmaSUG 2004 %Cox_PH - An enhancement of SAS PROC PHREG Hong (Lily) Zhang,
Robin Mogg		 8
PharmaSUG 2004 Automate Pharmacodynamic Analyses of Repeated Measure in Clinical Trials Using SAS Mixed Procedure Adeline Yeo,
Grace Li		 5
WUSS 2003 How to Get a Graph from a Complex Linear Model Stefanie J. Silva source 4
WUSS 2003 Regression Diagnostic Plots George C. J. Fernandez source 9
SESUG 2003 Statistical Analysis of Genotype X Environment Interaction in Agricultural Research K. Bondari source 6
WUSS 2002 A Randomization-Test Wrapper for SAS PROCs Christopher F. Ake,
David L. Cassell		 source 4
SEUGI 2002 Calculating the return on investment made in Analytical CRM - does it make business sense? [presentation] AJ Kruger source 27
SUGI 2002 A Proportional Odds/Hazards Approach to Analyzing Likert Scale Data Lynette K. Duncan,
James E. Dunn		 source 5
SUGI 2002 A Randomization-Test Wrapper for SAS PROCs David L. Cassell source 4
SUGI 2002 Automating the Building of 2nd and 3rd Order Interactions and the Construction of Hierarchical Logistic Regression Models Mazen Abdellatif,
Robert G. Anderson,
Domenic J. Reda		 source 4
SESUG 2001 A Simulation Study to Compare the Performance of Permutation Tests for Time by Group Interaction in an Unbalanced Repeated-Measures Design, Using Two Permutation Schemes Mark S. Litaker,
Bob Gutin		 source 5
SUGI 2001 A Macro Program for ANOVA or ANCOVA, Using PROC GLM or PROC MIXED Zaizai Lu,
David Shen		 source 4
SCSUG 2000 Repeated-Measures Analysis and PROC MIXED Shana Smith,
Torsten B. Neilands		 17
WUSS 2000 An Overview of remedial tools for collinearity in SAS Chong Ho Yu source 6
SEUGI 2000 SAS Software for the Analysis of Epidemiologic Data [presentation] Hans-Peter Altenburg source 39
PharmaSUG 2000 An Alternative to the Odds Ratio: A Method for Comparing Adjusted Treatment Group Effects on a Dichotomous Outcome P. Chris Holland 5
MWSUG 1999 REG, GLM, ANOVA: Which One? Why? How? Linda M. Quinn 6
MWSUG 1999 Using PROC MIXED in Hierarchical Linear Models: Examples from two- and three-level school-effect analysis, and meta-analysis research Sawako Suzuki,
Ching-Fan Sheu		 8
SUGI 1999 Fitting a Multisource Regression Model with Random Slopes, A Fisheries Application of SAS PROC MIXED Robert G. Downer,
Mark C. Benfield		 source 5
SUGI 1999 Modeling Event Count Data with PROC GENMOD and the SAS System Matthew J. Flynn source 6
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
SEUGI 1998 Complementary use of log-linear modelling and correspondence analysis in SAS software Jon Paul Laka,
Izaskun Astondoa		 source 18
NESUG 1997 Using Logistic Regression to Test for Interaction in the Presence of Zero Cells Lisa Suchower 10
SEUGI 1997 Weighted Poisson Analysis à la Goodman using SAS software Rian Vogelesang source 14
SUGI 1997 Introduction to Building a Linear Regression Model Leslie A. Christensen source 7
NESUG 1996 Using the SAS System for Continuous Quality Improvement Melissa A. Durfee 10
MWSUG 1995 Discussion of the Comparison of GLM and MIXED Procedures for a Repeated Measures Design: One Within and One Between Subjects Factor Michelle Secic 6
SUGI 1995 A Comparative Evaluation of Selected Statistical Software for Computing Various Categorical Analyses Nancy McDermott,
Cynthia White		 source 6
SUGI 1995 Karnaugh Maps, Interaction Effects and Creating Composite Dummy Variables for Regression Analysis in SAS Software Lawrence C. Marsh,
Karin Wells		 source 10
MWSUG 1994 Alternative Approaches to Mixed Linear Models George W. Pasdirtz 6
SEUGI 1994 Point and Interval Estimation of Risk and Rate Advancement Periods in Epidemiologic Studies Using SAS Software Annette Pfhalberg source 11
SUGI 1994 Automating the Plotting of Significant Effects in Analysis of Variance Matthew Grover,
Huixing Tang		 source 6
SUGI 1994 Introduction to Repeated Measures William G. LeBlanc source 9
SUGI 1994 Model Diagnostics for Three Factor Models Eric P. Smith,
Kyoungah See		 source 5
SCSUG 1993 Automating the Plotting of Significant Effects in Analysis of Variance Huixing Tang,
Matthew Grover		 14
SUGI 1993 Analysis-of-Variance Computing: Then and Now, with Reference to UnbalancedData Shayle R. Searle source 12
SCSUG 1992 Testing the Additivity Assumption in Repeated Measures Robert J. Zambarano 11
SEUGI 1992 PRPEST:A Flexible SAS Macro for Estimation of Risk Factor Impact in Epidemiologic Studies Hermann Brenner,
Olaf Gefeller		 source 9
SEUGI 1992 Using SAS Macros and PROC IML to Create Special Designs for Use in Generalised Linear Models John Hendrickx source 22
SUGI 1992 The Use of Logit Analysis: Pitfalls and SAS Tips William Chan source 3
SUGI 1989 Analysis of Nonreplicated Experiments with SAS/IML Software Michael R. Emptage source 5
SUGI 1989 Repeated-Measurement Designs: The Intricacies of Their Analysis with the SAS System Jean Hardy source 4
SUGI 1988 A Method for Hypotheses Testing in a Two-Way, Cross-classified Design with Missing Cells Kenneth L. Koonce,
Mattana Sanguanruang		 source 6
SUGI 1988 SOS: An Expert System Front-end for Analysis of Linear Models in the SAS System Michael P. Meredith,
Robert P. Yerex		 source 5
SUGI 1988 To Pool or Not to Pool in a Multicenter Clinical Trial Gregory T. Schwemer source 4
SUGI 1986 Using SAS Software in the Design and Analysis of Two-Level Fractional Factorial Experiments Joanne R. Wendelberger source 6
SUGI 1978 What Does GLM Do? The Case of the Missing Cell Rudolf J. Freund source 6

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