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210 papers and 3 presentations; 192 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
WUSS 2024 PROC BGLIMM: The Smooth Transition to Bayesian Analysis [presentation] Danny R. Modlin source 20
PharmaSUG CN 2024 Implementation on concentration-QTc modeling Daoqing Li,
Deli Cao		 source 20
PharmaSUG CN 2024 LSMEANS vs ESTIMATE in proc mixed Gloria Zhong,
Sukie Gao,
Wayne Yang		 source 12
SESUG 2023 Wald Tests in Mixed Models - a Warning David A. Dickey source 20
PHUSE EU 2022 Performance Traps in Multiple Imputation Analysis Using Mixed Model Repeated Measures [presentation] Piotr Karasiewicz source
video		 17
PHUSE EU 2022 Veranet: R Shiny Meets Network Meta-Analysis and Data Visualisation [presentation] Anton Schönstein source
video		 21
SGF 2021 Bayesian Analysis of GLMMs Using PROC BGLIMM Walter W. Stroup source
pdf		 25
SGF 2020 A Warning about Wald Tests David A. Dickey source 20
SGF 2020 Mixed-Effects Models and Complex Survey Data with the GLIMMIX Procedure L. Grisell Diaz-Ramirez,
Bocheng Jing		 source 10
SGF 2020 Modeling of Between - and Within-Subject Variances using Mixed Effects Location Scale (MELS) Models Qianheng Ma,
Donald Hedeker		 source 14
SGF 2020 Piecewise Latent Growth Curve Models to Test for Discontinuities in Disease Prevalence Trends Lin Yan source 10
SGF 2020 Simulating Data for Complex Linear Models Phil Gibbs,
Kathleen Kiernan		 source 20
MWSUG 2019 Legislative Action on Human Trafficking: Towards a Data-Driven Policy David J. Corliss 9
PharmaSUG 2019 PROC MIXED: Calculate Correlation Coefficients in the Presence of Repeated Measurements Qinlei Huang,
Radha Railkar		 source 16
SGF 2019 A Selective Overview of Panel Data with Applications in SAS Oral Capps source 26
SGF 2019 The Relationship Between Social Determinants of Health and Healthcare Utilization Ryan C. Butterfield,
Melissa Gottschalk,
Laura Soloway,
Paul A. LaBrec		 source 16
PHUSE EU 2018 Collinearity in Mixed Models John Hendrickx source
presentation source		 11
MWSUG 2018 Bootstrap Linear Mixed-Effects Models using SAS Procedures Adams Kusi Appiah 17
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 "Training Wheels" for learning mixed models YuTing Tian,
Russell M. Lavery		 source 20
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
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 How to Fit Longitudinal Data with Proc MCMC Maud Henion source
presentation source		 16
WUSS 2017 Analyzing Multiple Membership Hierarchical Data Using PROC GLIMMIX Maria Elsa Vazquez Arreola,
Jeffrey Wilson		 source 7
WUSS 2017 Modeling Longitudinal and Multilevel Data in SAS Niloofar Ramezani source 8
SGF 2017 Analyzing Correlated Data in SAS Niloofar Ramezani source 13
SGF 2017 Fitting Complex Statistical Models with NLMIXED and MCMC Procedures Robin High source 14
SGF 2017 Meta-Analysis of Human Trafficking in the United States David J. Corliss,
Heather Hill		 source 8
SESUG 2016 A Short Introduction to Longitudinal and Repeated Measures Data Analyses Leanne Goldstein source 19
MWSUG 2016 Fitting Complex Statistical Models with PROCs NLMIXED and MCMC Robin High 16
MWSUG 2016 The State of Human Trafficking in the Cincinnati Metropolitan Area - a Statistical Case Study David J. Corliss,
Heather M. Hill		 8
WUSS 2016 How to analyze correlated and longitudinal data? Niloofar Ramezani source 8
PharmaSUG 2016 Mixed Effects Models Yan Wang source 7
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 Bayesian Inference for Gaussian Semiparametric Multilevel Models Jason Bentley,
Cathy Yuen Yi Lee		 source
zip		 19
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
SESUG 2015 A SAS Macro to Investigate Statistical Power in Meta-analysis Jin Liu,
Fan Pan		 source 5
SESUG 2015 An Intermediate Guide to Estimating Multilevel Models for Categorical Data using SAS PROC GLIMMIX Whitney Smiley,
Elizabeth A. Leighton,
Zhaoxia Guo,
Mihaela Ene,
Bethany A. Bell		 source 16
SESUG 2015 Behavioral Trajectories: An Analysis of Growth Patterns and Predictors of Changes from Preschool to First Grade Jin Liu,
Fan Pan,
Yin Burgess,
Christine DiStefano		 source 11
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 Approximation methods and quadrature points in PROC NLMIXED: A simulation study using structured latent curve models Nate Smith,
Shelley A. Blozis		 source 10
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
SGF 2015 Advanced Techniques for Fitting Mixed Models Using SAS/STAT Software Kathleen Kiernan source 18
SGF 2015 Catering to Your Tastes: Using PROC OPTEX to Design Custom Experiments, with Applications in Food Science and Field Trials Cliff Pereira,
Randy Tobias		 source
zip		 11
SGF 2015 Modeling Effect Modification and Higher-Order Interactions: A Novel Approach for Repeated Measures Design Using the LSMESTIMATE Statement in SAS 9.4 Pronabesh DasMahapatra,
Ryan Black		 source
zip		 6
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
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
SESUG 2014 Modeling Cognitive Processes of Learning with SAS Procedures Isaac Y. Li,
Yi-Hsin Chen,
Chunhua Cao,
Yan Wang		 source 11
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
SGF 2014 A Stepwise Algorithm for Generalized Linear Mixed Models Nagaraj Neerchal,
Jorge Morel,
Xuang Huang,
Alain Moluh		 source 11
SGF 2014 An Intermediate Primer to Estimating Linear Multilevel Models Using SAS PROC MIXED Bethany A. Bell,
Whitney Smiley,
Mihaela Ene,
Genine L. Blue		 source 19
SGF 2014 Got Randomness? SAS for Mixed and Generalized Linear Mixed Models David A. Dickey source 12
SGF 2014 Modeling Loss Given Default in SAS/STAT Xiao Yao,
Jonathan Crook,
Galina Andreeva		 source 9
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
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
MWSUG 2013 Ideas and Examples in Generalized Linear Mixed Models David A. Dickey 12
SGF 2013 %MIXED_FIT: A SAS Macro to Assess Model Fit and Adequacy for Two-Level Linear Models Bethany A. Bell,
Mihaela Ene,
Whitney Smiley		 source
pdf		 8
SGF 2013 A Multilevel Model Primer Using SAS PROC MIXED Bethany A. Bell,
Jason A. Schoeneberger,
Mihaela Ene,
Whitney Smiley		 source 19
SGF 2013 A SAS Macro for Computing Pooled Likelihood Ratio Tests with Multiply Imputed Data Stephen Mistler source 10
SGF 2013 Growth Spline Modeling Eric Day,
Matthew Schuelke,
Robert Terry		 source
pdf		 9
SESUG 2012 %MIXED_FIT: A SAS Macro to Assess Model Fit and Adequacy for Two-Level Linear Models Mihaela Ene source 8
SESUG 2012 Random Effects Simulation for Sample Size Calculations Using SAS Random Effects Simulation source 11
PharmaSUG 2012 Computing Initial Values for Pharmacokinetic ML Nonlinear Regression via genetic algorithms and parallel genetic algorithms Francisco Juretig source 11
PharmaSUG 2012 Pattern-Mixture Models as Linear Combinations of Least Squares Means from MMRM with Delta Method Variance Estimation Bohdana Ratitch,
Michael O'Kelly		 source 15
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 MV_META: A SAS Macro for Multivariate Meta-Analysis Julie A. Gloudemans,
Corina M. Owens,
Jeffrey D. Kromrey		 source 15
SESUG 2011 Acknowledging the Unknown: A SAS Macro for Investigating Omitted Variable Bias in Two-Level Linear Models Jason A. Schoeneberger,
Bethany A. Bell,
Jeffrey D. Kromrey		 source 16
SESUG 2011 MV_META: A SAS Macro for Multivariate Meta-Analysis Julie A. Gloudemans source 12
PHUSE EU 2011 Estimation of relative potency in a 4-point parallel line assay Stefano Vezzoli source
presentation source		 11
MWSUG 2011 Interpreting the Differences Among LSMEANS in Generalized Linear Models Robin High 11
PharmaSUG 2011 CONTRAST and ESTIMATE Statements Made Easy: The LSMESTIMATE Statement Kathleen Kiernan,
Randy Tobias,
Phil Gibbs,
Jill Tao		 source 19
SGF 2011 CONTRAST and ESTIMATE Statements Made Easy: The LSMESTIMATE Statement Kathleen Kiernan,
Randy Tobias,
Phil Gibbs,
Jill Tao		 source 19
SGF 2011 PROC PANEL Vs. A FAST ALGORITHM FOR ESTIMATION OF UNBALANCED PANEL DATA MODELS WITH TWO FIXED EFFECTS Alan Ricardo da Silva,
Mariana Fernandes Teixeira,
Thaís Helena Fernandes Teixeira		 source 12
SGF 2011 Repeated Measures Analysis of Correlated Data with Multiple Responses Using SAS Anbuchelvi Jeyabslasingham,
Anpalaki J. Ragavan		 source 10
PHUSE EU 2010 Inference for the Location Shift in 3x3 Crossover Studies: the Median-Scaling Method Stefano Vezzoli source
presentation source		 5
MWSUG 2010 Ideas and Examples in Generalized Linear Mixed Models David A. Dickey 12
MWSUG 2010 Power to Detect Therapist Effects in Randomized, Controlled Trials of Interventions in Clinical Psychology Douglas Thompson,
Fary Cachelin,
Ruth Striegel-Moore,
Terry Wilson		 16
MWSUG 2010 PROC MIXED: Underlying Ideas with Examples David A. Dickey 19
MWSUG 2010 Using HPMIXED and Other SAS Procedures to Efficiently Analyze Large Dimension Registry Data Matthew Fenchel,
Gary McPhail,
Rhonda D. VanDyke		 19
PharmaSUG 2010 Linear Mixed Models in Clinical Trials using PROC MIXED Danyang Bing,
Xiaomin He		 12
SGF 2010 Dancing the Sample-Size Limbo with Mixed Models: How Low Can You Go? Bethany A. Bell,
Grant B. Morgan,
Jason A. Schoeneberger,
Brandon L. Loudermilk,
Jeffrey D. Kromrey,
John M. Ferron		 source 11
SGF 2010 Ideas and Examples in Generalized Linear Mixed Models David A. Dickey source 12
SGF 2010 Using the GLIMMIX Procedure to Model Hospital Quality Measured by CMS: Comparing City-Owned Hospitals, Other Safety Net Hospitals, and Hospitals for the Well-Insured Ronald B. Low source 11
SESUG 2009 A New Effect Modification P Value Test Demonstrated Manojkumar B Agravat source 14
SESUG 2009 PROC MIXED: Macro to assess fixed and random effects for significance using the Likelihood Ratio test and the approximate Mixture Method Barbara H. Bardenheier source 7
MWSUG 2009 Mixed Model Selection George C. J. Fernandez 19
NESUG 2009 Build Multilevel Model to Assess the Length to Inpatient Readmission Using SAS PROC MIXED Qingfeng Liang 13
SGF 2009 All the Cows in Canada: Massive Mixed Modeling with the HPMIXED Procedure in SAS 9.2 Tianlin Wang source 15
SGF 2009 Comparison of Features and Applications of Four Linear Models Procedures Larry W. Douglass source 19
SGF 2009 Parsimony vs. Complexity: A Monte Carlo Investigation of Hierarchical and Cross-Classified Modeling Using SAS PROC MIXED Bethany A. Bell,
Corina M. Owens,
Jeffrey D. Kromrey,
John M. Ferron		 source 12
WUSS 2008 User-friendly SAS Macro Application for performing all possible mixed model selection - An update George C. J. Fernandez source 19
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
PHUSE EU 2008 Statistics for Non-Statisticians Shambhavi Nayak source 10
MWSUG 2008 Visualization and the Improvement of Anodized Parts Using JMP Philip J. Ramsey,
Marie A. Gaudard,
Mia L. Stephens		 42
NESUG 2008 SAS Program for Bivariate Growth Curve with Kalman Filter Amy E. Begley,
Qianyu Dang,
Patricia R. Houck,
Sati Mazumdar		 6
SGF 2008 Building Mathematics-Achievement Models for Developed and Developing Countries: An Application of SAS to Large-Scale, Secondary Data Management and Analysis Ha Phan source 12
SGF 2008 Computational Algorithm for Estimation of Panel Data Models with Two Fixed Effects Alan Ricardo da Silva,
Patrick F. Alves		 source 10
SGF 2008 Old Versus New: A Comparison of PROC LOGISTIC and PROC GLIMMIX Rebecca Christofferson source 6
SGF 2008 PROC MIXED: Underlying Ideas with Examples David A. Dickey source 18
SESUG 2007 PROC MIXED: Underlying Ideas with Examples David A. Dickey source 19
PHUSE EU 2007 Reporting of NONMEM Models using S-PLUS Richard Pugh source 7
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 GLMM_SIM: A SAS Macro for Evaluating the Statistical Integrity of General Linear Mixed Models James T. Hess,
Melinda R. Hines,
Constance Kromrey,
Jeffrey D. Lee,
Reginald S. Luther,
Stephen L. Coraggio		 source 10
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 Population Pharmacokinetics Studies with Nonlinear Mixed Effects Modeling Zaizai Shen,
David Lu		 source 11
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
SESUG 2006 MLM_SIM: A SAS Macro for the Statistical Investigation of Mixed Models Jeffrey D. Kromrey source 15
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
PharmaSUG 2006 From GLM to GLIMMIX-Which Model to Choose? Patricia B. Cerrito 7
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 A Comparison of the MIXED Procedure and the GLIMMIX Procedure Jennifer L. Ferrell source 8
SUGI 2006 Fixed Effects Regression Methods in SAS Paul D. Allison source 20
SUGI 2006 METAPERM2: A SAS Macro for Permutation Tests of Linear Models in Fixed and Random Effects Meta-Analyses Jeffrey D. Kromrey,
Kristine Y. Hogarty		 source 10
MWSUG 2005 A Comparison Of Linear Mixed Models To Generalized Linear Mixed Models: A Look At The Benefits Of Physical Rehabilitation In Cardiopulmonary Patients Jennifer Ferrell 7
MWSUG 2005 Medicare Cost Estimation For Heart Disease Fariba Nowrouzi 11
WUSS 2005 A Comparison of Two Procedures to Fit Multi-Level Data: PROC GLM versus PROC MIXED MaryAnne DePesquo Hope source 7
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 Adopting New Techniques: Statistical Procedures to Determine the Agreement between two Laboratory Methods Ashley Peterson,
Larry W. Douglass		 13
NESUG 2005 Introducing the GLIMMIX Procedure for Generalized Linear Mixed Models Oliver Schabenberger 20
SUGI 2005 A Comparison of Two Procedures to Fit Multi-Level Data: PROC GLM versus PROC MIXED Erin D. Shannon,
MaryAnne DePesquo Hope		 source 7
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
SESUG 2004 Crossover Designs and Proc Mixed In SAS Hossein N. Yarandi source 11
SESUG 2004 Mixed Model Influence Diagnostics Oliver Schabenberger source 17
WUSS 2004 Mixed Model Influence Diagnostics Oliver Schabenberger source 17
PharmaSUG 2004 Automate Pharmacodynamic Analyses of Repeated Measure in Clinical Trials Using SAS Mixed Procedure Adeline Yeo,
Grace Li		 5
PharmaSUG 2004 Extending ODS Output by Incorporating Trellis Graphics from S-PLUS Robert Treder,
Jagrata Minardi		 12
PharmaSUG 2004 Generating Least Square Means, Standard Error, Observed Mean, Standard Deviation and Confidence Intervals for Treatment Differences using Proc Mixed Richann J. Watson 12
PharmaSUG 2004 Graph the R Matrix in Linear Mixed Model Jian Wu,
Peter Button		 8
PharmaSUG 2004 The Meta-Analysis (PROC MIXED) of Two Pilot Clinical Studies with a Novel Antidepressant Lev Sverdlov,
Park Ridge		 6
PharmaSUG 2004 Traditional Repeated Measures Analysis Versus Random Coefficients Models Using PROC MIXED Radhi Abdulnabi 9
SUGI 2004 Mixed Model Influence Diagnostics Oliver Schabenberger source 18
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
SUGI 2003 An Introduction to the Analysis of Mixed Models Dallas E. Johnson source 4
MWSUG 2002 Random Coefficient Model for Hazard Analysis Critical Control Points (HACCP) A Pilot Study Xinpeng (Tom) Wang,
Yating Sun,
Julie Caswell		 3
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
NESUG 2001 Power and Sample Size Determination for Linear Models John M. Castelloe 13
NESUG 2001 Replicate-Based Variance Estimation in a SAS Macro Julia L. Bienias 9
SESUG 2001 Individual Growth Analysis Using PROC MIXED Maribeth H. Johnson source 7
SESUG 2001 Power and Sample Size Determination for Linear Models John M. Castelloe source 13
SCSUG 2001 Individual Growth Analysis Using PROC MIXED Maribeth H. Johnson 7
SCSUG 2001 Power and Sample Size Determination for Linear Models John M. Castelloe,
Ralph G. O'Brien		 13
PharmaSUG 2001 Fitting Gompertz Nonlinear Mixed Model to Infancy Growth Data with SAS version 8 Procedure NLMIXED Cindy Q. Song,
Olga M. Kuznetsova		 8
PharmaSUG 2001 Power and Sample Size Determination for Linear Models John M. Castelloe 14
SUGI 2001 Approximations to Distributions of Test Statistics in Complex Mixed Linear Models Using SAS PROC MIXED G. Bruce Schaalje source 6
SUGI 2001 Power and Sample Size Determination for Linear Models John M. Castelloe,
Ralph G. O'Brien		 source 13
SCSUG 2000 Estimating Regression Models with Spatially-Correlated Errors Using the MIXED Procedure Sam Field 15
SCSUG 2000 Multi-Level Intervention Study Data and PROC MIXED Tom Bohman 13
PharmaSUG 2000 A SAS Tool for the Presentation and Statistical Analysis of Data from Bioavailability and Bioequivalence Studies Melvin S. Munsaka,
Carl R. Haske		 8
PharmaSUG 2000 Meta-Analysis with Linear and Nonlinear Multilevel Models Using PROC MIXED and PROC NLMIXED Eugene Komaroff,
Russell D. Wolfinger		 4
PharmaSUG 2000 Mixed Models Analysis Using JMP Software 4.0 George A. Milliken 6
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
SUGI 2000 Modeling Longitudinal Growth Data and Growth Percentiles with Polynomial Gompertz Model in SAS Software Inna Perevozskaya,
Olga M. Kuznetsova		 source 6
WUSS 1999 Exploring Enzyme-Linked Immunosorbent Assay (ELISA) Data with the SAS Analyst Application Stewart L. Fossceco,
Nathan A. Curtis		 source 9
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 Exploring Enzyme-Linked Immunosorbent Assay (ELISA) Data with the SAS Analyst Application Stewart L. Fossceco,
Nathan A. Curtis		 source 9
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
NESUG 1997 Estimation of Direct, Period and Carryover Effects in Crossover Studies Mitchell Kotler 7
WUSS 1996 Repeated Measures Analysis with the SAS System Kathleen Kierman source 10
WUSS 1996 SAS PROC MIXED to Fit Growth Curve Models: Application to a Longitudinal Group Randomization Study Biao Wm. Lu,
Sandra Wilson,
David Latini,
David Dayton		 source 6
SUGI 1996 Analysis of Unbalanced Mixed Model Data Ramon C. Littell source 6
NESUG 1995 Practical Consdierations in Estimating Linear Dose Response From A Phase I/II Titration Study With Subjects As Random Effects Virginia Fitzpatrick,
Ruth Swithenbank		 7
WUSS 1995 General Reliability and Intraclass Correlation Program (GRIP) Ron D. Hayes,
Eric Yu I. Wang,
Michael S. Sonksen		 source 4
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
MWSUG 1994 Alternative Approaches to Mixed Linear Models George W. Pasdirtz 6
SEUGI 1994 Graphical Extensions for Principal Component Analysis (Insight of a Dream PCA) Philippe Besse source 16
SEUGI 1994 Using PROC MIXED on Animal Growth Curves Some Initial Experiences Graham Healey source 10
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 Combined Estimates of Carryover Differences in Mixed-Model Procedure Louis Munyakazi,
Richard L. Hintz,
B. D. Selby		 source 4
SUGI 1994 Mixed Model Analysis of Data: Transition from GLM to MIXED Ramon C. Littell source 8
MWSUG 1993 Common Industrial Applications of Mixed Models Bob Obenchain 10
SEUGI 1993 A New Look at the Facilities in PROC MIXED James L. Roger source 12
SESUG 1993 Repeated Measures Using PROC MIXED Instead of PROC GLM James H. Roger,
Michael Kenward		 10
SCSUG 1992 Testing the Additivity Assumption in Repeated Measures Robert J. Zambarano 11
SEUGI 1991 An Example of the Use of Historical Information in the Analysis of Pharmaceutical Screening Trials Egbert Biesheuvel,
R. A. J. Wixley		 source 9
SUGI 1991 Confidence Intervals for Contrasts in the Unbalanced Analysis of Variance Using SAS/IML Software John Ilgenfritz,
Anand K. Seth		 source 6
SUGI 1990 Analyzing and Reporting Fixed Effects in the Real World Christopher S. McFarland source 5
SUGI 1990 Computation of Variances of Functions of Parameter Estimates for Mixed Models in the GLM Procedure Ramon C. Littell,
Stephen B. Linda		 source 8
SEUGI 1989 Metaanalysis Objectives And Methods Jean-Claude Peyrieux source 6
SUGI 1989 Multivariate Models for the Analysis of Crossover Experiments Vernon M. Chinchilli,
Ronald K. Elswick		 source 5
SUGI 1989 Outlier Selection in Non-11D Linear Models with Applications to Variance Components Thomas Gerig,
Gerardo I. Hurtado		 source 5
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 1987 Estimation of Variance Components in Mixed Factorial Models Including Model-based Diagnostics Ronald H. Bremer,
John W. Green,
Ronald R. Hocking		 source 6
SUGI 1987 Variance Component Estimation with the SAS System Ramon C. Littell,
Barbara G. McCutchan		 source 6
SUGI 1986 Mixed Model Analyses with the SAS System Ramon C. Littell source 8
SUGI 1984 Computing for Unbalanced Repeated Measures Experiments Kenneth N. Berk source 7
SUGI 1983 A Diagnostic Tool for Mixed Models with Application to Negative Estimates of Variance Components .. Ronald R. Hocking source
SUGI 1982 Approaches to Estimation and Testing in the Mixed Model R. Kirk Steinhorst source
SUGI 1982 Parametric and Nonparametric Multiple Comparisons Using SAS Chandu M. Patel source 6
SUGI 1981 Estimation of Fixed Effects in Mixed Models with Unbalanced Data Walter R. Harvey source 7
SUGI 1981 On-line Estimation in Mixed Linear Models William M.Sallas source
SUGI 1981 The Cell Means Model: Evaluating GLM Type III and IV Sums of Squares for Linear Models with Missing Cells Richard L. Miller source 8
SUGI 1979 New Features in GLM and VARCOMP James H. Goodnight source 10
SUGI.ONE 1976 A Comparison of BMD, SAS and SPSS T. Papaioannou,
G.P.H. Styan,
L.L. Ward		 source 21

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