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covariance structure

147 papers and 4 presentations; 135 titles.

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Conference × Year × Title × Authors Extras Pages
PharmaSUG CN 2026 Handling Missing Data in Analgesia Clinical Trials and Corresponding SAS Implementation Jingbo Zhu,
Jiehan Zhang		 source 17
PHUSE EU 2025 GLMM and GEE for Categorical Repeated Measures - Linking SAS and R Miriam Amor source
presentation source		 16
MWSUG 2025 PROC BGLIMM: The Smooth Transition to Bayesian Analysis Danny R. Modlin source 57
SESUG 2025 PROC BGLIMM: The Smooth Transition to Bayesian Analysis Danny R. Modlin 57
WUSS 2025 PROC BGLIMM: The Smooth Transition to Bayesian Analysis [presentation] Danny R. Modlin source 57
PharmaSUG 2025 An End-to-End Workflow for TFL Generation using R: MMRM Applications and Comparative Insights with SAS Kai Lei,
Jiaqiang Zhu,
Margaret Huang		 source 14
PharmaSUG 2025 Mastering the Maze of Oncology Endpoints: A Unified SAS Approach for Randomized Controlled Trial Analysis Yuxin Wang,
Kelly Chao,
Wenqing Yu,
Hongbing Jin		 source 11
PHUSE EU 2024 Leveraging Bayesian Posterior Probability for Analysing Treatment Effects in Clinical Trials: A Statistical Programmer's Guide Vismaya Kondassam Veedu source
presentation source		 7
SESUG 2024 PROC BGLIMM: The Smooth Transition to Bayesian Analysis Danny R. Modlin source 9
WUSS 2024 PROC BGLIMM: The Smooth Transition to Bayesian Analysis [presentation] Danny R. Modlin source 20
PharmaSUG 2024 Estimating Time to Steady State Analysis in SAS Richard Moreton,
Lata Maganti		 source 8
PHUSE EU 2022 Performance Traps in Multiple Imputation Analysis Using Mixed Model Repeated Measures [presentation] Piotr Karasiewicz source
video		 17
PHUSE EU 2021 PROC MIXED: A Complicated Procedure in Simple Words [presentation] Kateryna Fedoryshyna source
video		 21
PHUSE US 2021 Confused with PROC MIXED? Find Out What is the Best Model Savithri Jajam,
Vamshi Matta		 source
video
presentation source		 7
PharmaSUG 2021 SAS Proc Mixed: A Statistical Programmer-s Best Friend in QoL Analyses Janaki Devi Manthena,
Varsha Korrapati,
Chiyu Zhang		 source 9
SGF 2020 Practical Geospatial Analysis of Open and Public-Use Data Pradeep Mohan source 20
SGF 2020 Simulating Data for Complex Linear Models Phil Gibbs,
Kathleen Kiernan		 source 20
PHUSE EU 2019 Mixed Model Repeated Measures (MMRMs) Mrudula Suryawanshi source
presentation source		 19
PharmaSUG 2019 PROC MIXED: Calculate Correlation Coefficients in the Presence of Repeated Measurements Qinlei Huang,
Radha Railkar		 source 16
SGF 2019 Analyzing Structural Causal Models using the CALIS Procedure Banoo Madhanagopal,
John Amrhein		 source 23
SGF 2019 Causal Analyses Using Structural Equation Models Banoo Madhanagopal,
John Amrhein		 source 23
SGF 2019 Introducing the BGLIMM Procedure for Bayesian Generalized Linear Mixed Models Amy Shi,
Fang K. Chen		 source 20
SGF 2019 Introducing the MBC Procedure for Model-Based Clustering David Kessler source 21
SGF 2019 Monitoring the Relevance of Predictors for a Model Over Time Ming-Long Lam source 16
PHUSE EU 2018 Collinearity in Mixed Models John Hendrickx source
presentation source		 11
MWSUG 2018 Tips, Tricks, and Traps on Longitudinal Data Analysis with Discrete and Continuous Times Brandy R. Sinco,
Edith Kieffer,
Michael S. Spencer,
Gray Ficker,
Gretchen Piatt		 20
WUSS 2018 Modeling Heterogeneous Within-Subject Variability Madeline Craft,
Shelley A. Blozis		 source 8
SGF 2018 Insights into Using the GLIMMIX Procedure to Model Categorical Outcomes with Random Effects Kathleen Kiernan source 23
SGF 2018 Using SAS for Multiple Imputation and Analysis of Longitudinal Data Patricia A. Berglund source 24
SCSUG 2016 An Ad Hoc Method for Computing Pseudo Effect Size for Mixed Models Kathryn G. Tippey,
Michael T. Longnecker		 source 7
SESUG 2016 A Short Introduction to Longitudinal and Repeated Measures Data Analyses Leanne Goldstein source 19
MWSUG 2016 Fitting Your Favorite Mixed Models with PROC MCMC Fang K. Chen,
Gordon Brown,
Maura E. Stokes		 27
WUSS 2016 Fitting Your Favorite Mixed Models with PROC MCMC Fang K. Chen source 27
WUSS 2016 How to analyze correlated and longitudinal data? Niloofar Ramezani source 8
SGF 2016 A Short Introduction to Longitudinal and Repeated Measures Data Analyses Leanne Goldstein source 19
SGF 2016 Analyzing Non-Normal Binomial and Categorical Response Variables under Varying Data Conditions Niloofar Ramezani source 16
SGF 2016 Fitting Your Favorite Mixed Models with PROC MCMC Gordon Brown,
Fang K. Chen,
Maura E. Stokes		 source 27
SGF 2016 Multiple-Group Multiple Imputation: An Empirical Comparison of Parameter Recovery in the Presence of Missing Data using SAS Patricia Rodríguez de Gil,
Jeffrey D. Kromrey		 source 15
SGF 2016 Tips and Strategies for Mixed Modeling with SAS/STAT Procedures Phil Gibbs source 21
MWSUG 2015 Advanced Techniques for Fitting Mixed Models Using SAS/STAT Software Jill Tao,
Kathleen Kiernan,
Phil Gibbs		 18
MWSUG 2015 How to Build a Hierarchical Mixed Model in SAS Sara Burns,
Amit Amin,
Eric Novak		 8
PHUSE EU 2015 Generating Multiple Parameter Reports into Single Reports Using %Do Loop and CALL SYMPUTX Krishna Gohil source
presentation source		 5
WUSS 2015 A Short Introduction to Longitudinal and Repeated Measures Data Analyses Leanne Goldstein source 19
WUSS 2015 Advanced Techniques for Fitting Mixed Models Using SAS/STAT Software Phil Gibbs,
Jill Tao,
Kathleen Kiernan		 source 18
WUSS 2015 Sample Size Convergence of Denominator Degrees of Freedom Method Options in SAS PROC MIXED Timothy Banh source 13
PharmaSUG CN 2015 Hands-on Tutorial for Piecewise Linear Mixed-effects Models Using SAS PROC MIXED Qinlei Huang 15
PharmaSUG 2015 MMRM: Macro for Selecting Best Covariance Structure with the Method of Interest Linga Reddy Baddam,
Sudarshan Reddy Shabadu,
Chunxue Shi		 source 7
SGF 2015 Advanced Techniques for Fitting Mixed Models Using SAS/STAT Software Kathleen Kiernan source 18
SGF 2015 Multilevel Models for Categorical Data Using SAS PROC GLIMMIX: The Basics Mihaela Ene,
Bethany A. Bell,
Genine L. Blue,
Elizabeth Leighton		 source 12
SGF 2015 Random vs. Fixed Effects: Which Technique More Effectively Addresses Selection Bias in Observational Studies Jessica Navratil-Strawn,
Stephen Hartley,
Ronald J. Ozminkowski		 source
zip		 8
SESUG 2014 Multilevel Models for Categorical Data Using SAS PROC GLIMMIX: The Basics Mihaela Ene,
Elizabeth A. Leighton,
Genine L. Blue,
Bethany A. Bell		 source 12
PHUSE EU 2014 Backward Selection: Immunity Test of Covariates Prathamesh Athavale source
presentation source		 10
PharmaSUG 2014 A Parameterized SAS Macro to Select an Appropriate Covariance Structure in Repeated Measures Data Analysis Using PROC MIXED Leela Aertker,
Paul Nguyen,
Charity Quick		 source 3
SGF 2014 An Intermediate Primer to Estimating Linear Multilevel Models Using SAS PROC MIXED Bethany A. Bell,
Whitney Smiley,
Mihaela Ene,
Genine L. Blue		 source 19
WUSS 2013 Using PROC NLMIXED to Fit Correlated Residual Error Structures in Nonlinear Mixed Models Shelley A. Blozis,
Jeffrey Harring		 source 5
SESUG 2013 An Intermediate Primer to Estimating Linear Multilevel Models Using SAS PROC MIXED Bethany A. Bell,
Whitney Smiley,
Mihaela Ene,
Phillip R. Sherlock,
Genine L. Blue		 source 13
PHUSE EU 2013 Around the World in Three Statistical Models: Determing the Level of Measurement Invariance Across Countries of a PRO Instrument Dirk Heerwegh source
presentation source		 29
PHUSE EU 2013 Using PROC GENMOD to Analyses Ratio to Placebo in Change of Dactylitis Imgard Hollweck source
presentation source		 9
SGF 2013 Modeling Change over Time: A SAS Macro for Latent Growth Curve Modeling Pei-Chin Lu,
Robert Pearson		 source 12
SESUG 2012 Tips and Strategies for Mixed Modeling with SAS/STAT Procedures Kathleen Kiernan,
Jill Tao,
Phil Gibbs		 source 18
MWSUG 2012 Survival of the Milkman - How Modern Analytics is Helping an Old Fashioned Business Thrive Bruce Bedford 13
MWSUG 2012 Tips and Strategies for Mixed Modeling with SAS/STAT Procedures Kathleen Kiernan,
Jill Tao,
Phil Gibbs		 18
SGF 2012 Tips and Strategies for Mixed Modeling with SAS/STAT Procedures Kathleen Kiernan,
Jill Tao,
Phil Gibbs		 source 18
SESUG 2011 Breastfeeding in Developing Countries: A Case Study of Nepalese Children Paerwen Paerhate,
George Mason		 source 4
PHUSE EU 2011 Use of early longitudinal viral load as a surrogate to the virologic endpoint in Hepatitis C Igwebuike Enweonye source
presentation source		 12
MWSUG 2011 A Macro to Estimate Sample-size Using the Non-Centrality Parameter of a Non-Central F-Distribution Matthew C. Fenchel,
Raouf S. Amin,
Rhonda D. VanDyke		 20
SGF 2011 Repeated Measures Analysis of Correlated Data with Multiple Responses Using SAS Anbuchelvi Jeyabslasingham,
Anpalaki J. Ragavan		 source 10
SGF 2011 Using SAS PROC TCALIS for Multigroup Structural Equation Modeling with Mean Structures Fei Gu,
Wei Wu		 source 16
PharmaSUG 2010 Dynamic Determination of Mixed Model Covariance Structures in Double-blind Clinical Trials Matthew Davis 7
SESUG 2009 Streamlining Data Analysis Edzard van Santen source 4
MWSUG 2009 Mixed Model Selection George C. J. Fernandez 19
SGF 2009 Comparison of Features and Applications of Four Linear Models Procedures Larry W. Douglass source 19
WUSS 2008 User-friendly SAS Macro Application for performing all possible mixed model selection - An update George C. J. Fernandez source 19
NESUG 2008 SAS Macro for Calculating Sample Size and Power on GLM Models with Correlated Binary Outcomes Qianyu Dang,
Patricia R. Houck,
Sati Mazumdar		 5
SGF 2008 Applying SAS Mixed-Model Procedures to Educational-Assessment Data Brian Patterson source 8
SGF 2008 Data Mining Application of Non-Linear Mixed Modeling in Water Quality Analysis Anpalaki J. Ragavan source 14
MWSUG 2007 RANDOM and REPEATED statements - How to Use Them to Model the Covariance Structure in Proc Mixed Charlie Liu 11
WUSS 2007 Time Series Cross Sectional Analysis of Total Nitrogen Concentration in Truckee River, Nevada Using SAS Anpalaki J. Ragavan source 11
SCSUG 2007 Individual Growth Analysis Using PROC MIXED Maribeth H. Johnson 10
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 Regression Splines with Longitudinal DATA Chan-Hee Gossett,
Jeff M. Simpson,
Pippa M. Jo		 source 6
SGF 2007 Repeated Measures Analysis with Clustered Subjects Ramon C. Littell source 11
MWSUG 2006 All Possible Model Selection in Proc Mixed - A SAS macro application George C. J. Fernandez 19
PHUSE EU 2006 Analysis of incomplete two-period crossover trials with SAS PROC MIXED Jochen Müller-Cohrs source 8
SESUG 2006 Individual Growth Analysis Using PROC MIXED Individual Growth source 10
WUSS 2006 Model Selection Methods in PROC MIXED George C. J. Fernandez source 19
WUSS 2006 PROC GENMOD with GEE to Analyze Correlated Outcomes Data Using SAS Tyler C. Smith,
Besa Smith		 source 14
PharmaSUG 2006 A SAS Macro to Find the Best Fitted Model for Repeated Measures Using PROC MIXED Jingjing Wang 8
PharmaSUG 2006 Analyzing Ordinal Repeated Measures Data Using SAS Bin Yang 8
SUGI 2006 %hlmdata and %hlmrmpower: Traditional Repeated Measures vs. HLM for Multilevel Longitudinal Data Analysis?Power and Type I Error Rate Comparison Hua Fang source 11
SUGI 2006 Analyzing Multivariate Longitudinal Data Using SAS Feng Gao,
Chengjie Xiong,
Paul A. Thompson,
J. Philip Miller		 source 9
SUGI 2006 Exploratory or Confirmatory Factor Analysis? Diana D. Suhr source 17
WUSS 2005 Introducing the GLIMMIX Procedure for Generalized Linear Mixed Models Oliver Schabenberger source 20
WUSS 2005 Using Proc Mixed to Model Daytime Log-Cortisol Slopes Eric Neri,
Helena Chmura Kraemer,
Arthur M. Noda,
Yung Wang		 source 4
NESUG 2005 Introducing the GLIMMIX Procedure for Generalized Linear Mixed Models Oliver Schabenberger 20
SUGI 2005 Guidelines for Selecting the Covariance Structure in Mixed Model Analysis Charles D. Kincaid source 8
SUGI 2005 Introducing the GLIMMIX Procedure for Generalized Linear Mixed Models Oliver Schabenberger source 20
SUGI 2005 Testing the Hypothesis of a Kroneckar Product Covariance Matrix in Multivariate Repeated Measures Data Anuradha Roy,
Ravindra Khattree		 source 11
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
PharmaSUG 2004 Automate Pharmacodynamic Analyses of Repeated Measure in Clinical Trials Using SAS Mixed Procedure Adeline Yeo,
Grace Li		 5
PharmaSUG 2004 Graph the R Matrix in Linear Mixed Model Jian Wu,
Peter Button		 8
PharmaSUG 2004 Making Model Selection in Linear Mixed-Effects Models An Easy Process: A SAS Macro Procedure Henry Cheng,
Yuli Xie,
Elizabeth Reinbolt		 4
PharmaSUG 2004 Traditional Repeated Measures Analysis Versus Random Coefficients Models Using PROC MIXED Radhi Abdulnabi 9
SUGI 2004 Fitting Longitudinal Mixed Effect Logistic Regression Models with the NLMIXED Procedure Peter H. Van Ness,
John R. O'Leary,
Amy L. Byers,
Terri R. Fried,
Joel A. Dubin		 source 7
SUGI 2004 Repeated Measures Modeling with PROC MIXED E. Barry Moser source 20
SESUG 2003 Comparison of PROC MIXED and PROC GLM for Analysis of Repeated Measures Data Hossein N. Yarandi source 6
PharmaSUG 2003 A SAS Macro to Automate The Covariance Structure Determination in Repeated Measures Data Analysis with Mixed Procedure Don (Dongguang) Li 4
PharmaSUG 2003 Parameter estimation for incomplete bivariate longitudinal data in clinical trials Naum M. Khutoryansky 6
PharmaSUG 2003 Using Model Fitting Information and PROC PLOT to Select the Type of Variance-Covariance Structure for Repeated Measures Radhi Abdulnabi 8
MWSUG 2002 Using Model Fitting Information and PROC PLOT to Select the Type of Varianc-Covariance Structur Radhi Abdulnabi 7
SUGI 2002 A Macro for Examining the Consequences of Error Structure Misspecifications John M. Ferron,
Kristine Y. Hogarty,
Melinda Hess,
Jeanine L. Romano		 source 6
SUGI 2002 Individual Growth Analysis Using PROC MIXED Maribeth H. Johnson source 7
MWSUG 2001 Using The SAS Mixed Procedure to Analyze the Repeated Measures Data Hongsen Zhou 9
SESUG 2001 Individual Growth Analysis Using PROC MIXED Maribeth H. Johnson source 7
SCSUG 2001 Individual Growth Analysis Using PROC MIXED Maribeth H. Johnson 7
SUGI 2001 Approximations to Distributions of Test Statistics in Complex Mixed Linear Models Using SAS PROC MIXED G. Bruce Schaalje source 6
SCSUG 2000 Estimating Regression Models with Spatially-Correlated Errors Using the MIXED Procedure Sam Field 15
SCSUG 2000 Repeated-Measures Analysis and PROC MIXED Shana Smith,
Torsten B. Neilands		 17
PharmaSUG 2000 Running Reports Using the PROC Mixed Procedure Marina V. Kungurtseva 8
SUGI 2000 A Primer in Spatial Simulation with PROC SIM2D Robert G. Downer source 3
SUGI 2000 Custom Design of Complicated Block Experiments G. Bruce Schaalje,
Chris H. Bodily,
Bruce J. Collings		 source 4
SUGI 2000 Mixed-Up Mixed Models: Things That Look Like They Should Work But Don't, and Things That Look Like They Shouldn't Work But Do Robert M. Hamer,
Pippa M. Simpson		 source 8
SESUG 1999 Analysis of Longitudinal Data: Comparison between PROC GLM and PROC MIXED Maribeth H. Johnson source 6
MWSUG 1999 Longitudinal Data Analysis Repeated-Measure ANOVA and Mixed Models Nancy E. Briggs,
Ching-Fan Sheu		 6
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
MWSUG 1998 Using PROC MIXED To Analyze a Repeated Measures Design Keith Dunnigan 6
WUSS 1997 Estimation of Shelf-Life and the Minimum Effective Dose Using PROC MIXED Louis Munyakazi source 6
SESUG 1997 Analysis of Repeated Measures and Longitudinal Data Jane Pendergast 8
SUGI 1997 Model Selection in Linear Mixed Effects Models Using SAS PROC MIXED Long Ngo,
Richard Brand		 source 6
SUGI 1997 Use of PROC MIXED in the Analysis of Repeated Measures Data from a Clinical Trial in Obsessive Compulsive Disorder William Bushnell,
Martin Steiner		 source 6
NESUG 1996 BIOEQ4: Bioequivalence Macro to Create both Table and SAS data set according to the FDA Bioequivalence Guidelines Issued in 1992 Mary Kay McPherson 6
WUSS 1996 Repeated Measures Analysis with the SAS System Kathleen Kierman source 10
SUGI 1996 Estimating and Evaluating Correlation Structures in Repeated Measures Designs Using the GLM and MIXED Procedures Maribeth H. Johnson,
Tom Baranowski		 source 5
SUGI 1996 Repeated Measures - A Better way? Edith Flaster source 10
SUGI 1996 Test of Hypotheses in Repeated Measures Models Under General Antedependence Covariance Structures in SAS Software Raul E. Macchiavelli,
E. Barry Moser		 source 4
SEUGI 1995 The Analysis of Cross-Over Study with Repeated Measures within PEriods by Using Different Covariance Structures Juhani Tuominen,
Sanna Hinkka		 source 12
SUGI 1995 Comparing the SAS GLM and MIXED Procedures for Repeated Measures Ming Chang,
Russell D. Wolfinger		 source 11
SUGI 1995 Conducting Linear Growth Curve Analysis with the SAS System Laura Ichikawa,
William E. Barlow		 source 6
SUGI 1995 Modeling Variation in Repeated Measures Data Ramon C. Littell source 5
SUGI 1994 A Comparison of the GLM, IML, and MIXED Procedures for Use in Spatial Statistical Analyses William J. Price,
Bahman Shafii		 source 6
SUGI 1994 Mixed Model Analysis of Data: Transition from GLM to MIXED Ramon C. Littell source 8
SEUGI 1993 EEG Multi-variate Traces Analysed Using PROC MIXED Tracy Parker source 10
SUGI 1992 Statistical Simulations Using the CALIS Procedure David P. MacKinnon source 5
SUGI 1992 Using SAS Software to Evaluate the Power of Alternative Data Analytic Methods for Repeated Measures Designs Thomas C. Chenier source 6
SUGI 1990 The Analysis of Data from 2 X 2 Crossover Trials with Baseline Measurements Joe DiGennaro,
William C. Huster		 source 6
SUGI 1989 A SAS/IML Matrix Program to Estimate Indirect Effects and Their Standard Errors David P. MacKinnon,
Eric Yu I. Wang		 source 6
SUGI 1989 Multivariate Models for the Analysis of Crossover Experiments Vernon M. Chinchilli,
Ronald K. Elswick		 source 5
SUGI 1988 Repeated Measures Analysis with the SAS System Ramon C. Littell,
Jane Pendergast		 source 7
SUGI 1986 Inference from the Incomplete Longitudinal Design: A Collection of SAS Macros James Rochon source 6

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