| PharmaSUG CN |
2026 |
A Comprehensive R Shiny Application for Pharmacokinetic Analysis |
Keyi Zhang |
source |
17 |
| PharmaSUG CN |
2026 |
Handling Missing Data in Analgesia Clinical Trials and Corresponding SAS Implementation |
Jingbo Zhu,
Jiehan Zhang |
source |
17 |
| PharmaSUG |
2026 |
Modernizing Clinical Research Analytics with Cloud-Optimized SAS Procedures |
Jim Box,
Mary Dolegowski |
source |
5 |
| PHUSE US |
2026 |
Framework for Incorporating Estimands within the Statistical Analysis Plan |
Inderjeet Arora |
source
presentation source |
9 |
| PHUSE US |
2026 |
Multiple Sclerosis Trials Unpacked: Standards, Endpoints and Programming Experience |
Daryna Teteriuk |
source
presentation source |
12 |
| 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 APAC |
2026 |
Mixed Models & Measured Outcomes: R Tips from the Clinical Trenches |
Keyur Shah |
source
presentation source |
5 |
| PHUSE APAC |
2026 |
Unlock Deeper Clinical Insights: A Unified Approach to Data Analysis with SAS, R, and Python |
Pavan Kallurkar |
source
presentation source |
7 |
| PHUSE EU |
2025 |
Bridging Languages: Building Integrated Analytical Tools with SAS, R, and Python for Clinical Data |
Margarethe Povey |
source
presentation source |
7 |
| 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 |
PROC BGLIMM: The Smooth Transition to Bayesian Analysis |
Danny R. Modlin |
source |
57 |
| SESUG |
2025 |
Comparing analysis method implementations in software (CAMIS) |
Brian K. Varney |
|
4 |
| SESUG |
2025 |
Navigating Model Choice in SAS: A Case-Based Decision-Support Framework for PROC REG, GLM, GENMOD, and MIXED |
Sriya Venkat |
|
10 |
| 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 |
AI-Assisted Transition: from SAS to RStudio for PK Summary Analysis |
Shiqi Lin |
source |
9 |
| 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 |
Handling Missing Data in External Control Arms: Best Practices, Recommendations, and SAS Code Examples |
Yutong Zhang |
source |
6 |
| PharmaSUG |
2025 |
Incorporating Frailty into Time-to-Event Analysis: A Practical Approach with R frailtypack |
Sunil Kumar Pusarla,
Avani Reddy Alla |
source |
9 |
| 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 |
| PharmaSUG |
2025 |
Programming Perspectives for Efficient and Accurate C-QTc Analysis |
Lingjie Zhang,
Lata Maganti,
Richard Moreton,
Runcheng Li |
source |
11 |
| 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 |
| PHUSE EU |
2024 |
A programmer's introduction to modelling with proc mixed, focusing on how to debug and validate, common mistakes and how to interpret the output |
George Gibson |
source
presentation source |
6 |
| PHUSE EU |
2024 |
A Tutorial for JFM Analysis in SAS for Modelling Recurrent Events and Death |
Edyta Winciorek |
source
presentation source |
9 |
| 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 |
Developing a SAS Macro for ISNI: Assessing Missing Data Sensitivity Beyond MAR Assumptions |
Bocheng Jing,
L. Grisell Diaz-Ramirez,
W. John Boscardin |
source |
16 |
| WUSS |
2024 |
PROC BGLIMM: The Smooth Transition to Bayesian Analysis [presentation] |
Danny R. Modlin |
source |
20 |
| PharmaSUG CN |
2024 |
Application of I&I Late Phase in Programming |
Renxiang Wang |
source |
15 |
| PharmaSUG CN |
2024 |
Implementation on concentration-QTc modeling |
Daoqing Li,
Deli Cao |
source |
20 |
| PharmaSUG CN |
2024 |
Implementing the treatment policy estimation for continuous variable with multiple imputation |
Andy Sun |
source |
17 |
| PharmaSUG CN |
2024 |
LSMEANS vs ESTIMATE in proc mixed |
Gloria Zhong,
Sukie Gao,
Wayne Yang |
source |
12 |
| PharmaSUG |
2024 |
Bayesian Models with the Power Prior Using PROC BGLIMM |
Yi Gong,
Fang K. Chen |
source |
15 |
| PharmaSUG |
2024 |
Estimating Time to Steady State Analysis in SAS |
Richard Moreton,
Lata Maganti |
source |
8 |
| PHUSE US |
2024 |
Analysis of Same Objective - Different SAS Procedures: How to Choose a SAS Procedure Wisely for a Statistical Analysis? |
Pradeep Acharya,
Ephicacy Lifescience |
source
presentation source |
9 |
| SESUG |
2023 |
%modelselect: A macro for automatically selecting statistical models based on fit statistics |
William B. Smith |
source |
7 |
| SESUG |
2023 |
Longitudinal Analysis of Marital Therapy's Impact on Intimacy in Heterosexual Couples |
Yaa Awuah,
Mostafa Zahed |
source |
19 |
| SESUG |
2023 |
Wald Tests in Mixed Models - a Warning |
David A. Dickey |
source |
20 |
| PharmaSUG |
2023 |
Meta-Analysis in R |
Lin Gu |
source |
8 |
| PharmaSUG |
2023 |
Sensitivity Analysis for Missing Data Using Control-based Pattern Imputation |
Jun Feng,
Jingmin Liu |
source |
7 |
| PHUSE EU |
2022 |
Harnessing Routinely Generated git, github and Package-specific Metadata to Build a Portal into Open-source Projects [presentation] |
Mathieu Cayssol,
James Black |
source
video |
18 |
| 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 |
| PharmaSUG |
2022 |
Measuring Reproducibility and Repeatability of an AI-based Quantitative Clinical Decision Support Tool Having a Medical Decision Point |
Douglas Milikien |
source |
9 |
| PHUSE EU |
2021 |
PROC MIXED: A Complicated Procedure in Simple Words [presentation] |
Kateryna Fedoryshyna |
source
video |
21 |
| PHUSE EU |
2021 |
Software Evolutions are Inevitable: Phase Your Coding evolution to Modern Clinical Trial Analytics by Using both Old/New Techniques in a Modern SAS Platform [presentation] |
Olivier Bouchard,
Pritesh Desai |
source
video |
19 |
| 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 |
2021 |
Bayesian Analysis of GLMMs Using PROC BGLIMM |
Walter W. Stroup |
source
pdf |
25 |
| SGF |
2020 |
A Level Headed Approach to the METHOD=FASTQUAD Option in the GLIMMIX Procedure |
Sidney J. Hann |
source |
11 |
| SGF |
2020 |
A Warning about Wald Tests |
David A. Dickey |
source |
20 |
| SGF |
2020 |
Estimating Unknown Change Points and Variation Using SAS |
Depeng Jiang,
Lin Yan,
Zhongyuan Zhang,
Shaoping Jiang |
source |
14 |
| SGF |
2020 |
Fitting Statistical Models with PROC MCMC |
Mark Ghamsary |
source |
26 |
| SGF |
2020 |
Mixed-Effects Models and Complex Survey Data with the GLIMMIX Procedure |
L. Grisell Diaz-Ramirez,
Bocheng Jing |
source |
10 |
| SGF |
2020 |
Model-Based Risk-Adjustment in Clinical Outcome Research |
Jiming Fang,
Feng Qiu |
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 |
| SGF |
2020 |
Time After Time: D-I-D and ITS Models in SAS |
Margaret Warton |
source |
21 |
| SGF |
2020 |
Transdermal Medicine - Challenges and Solutions with SAS |
Marina Komaroff |
source |
14 |
| PHUSE EU |
2019 |
Bioequivalence Testing for Highly Variable Drug Products (HVDPs) |
James R. Johnson |
source
presentation source |
9 |
| PHUSE EU |
2019 |
Mixed Model Repeated Measures (MMRMs) |
Mrudula Suryawanshi |
source
presentation source |
19 |
| PHUSE EU |
2019 |
The Promise of Wearable Technology in Clinical Trials: A Proof of Concept to Deliver it? |
Jennifer Bradford |
source
presentation source |
11 |
| SESUG |
2019 |
Generalized Linear Mixed Model Approach to Time-to-Event Data with Censored Observations |
Censored Observations |
source |
9 |
| MWSUG |
2019 |
Legislative Action on Human Trafficking: Towards a Data-Driven Policy |
David J. Corliss |
|
9 |
| WUSS |
2019 |
Implementing the Hamiltonian Monte Carlo Sampling algorithm in PROC MCMC |
Elsa Vazquez Arreola |
source |
10 |
| PharmaSUG |
2019 |
PROC MIXED: Calculate Correlation Coefficients in the Presence of Repeated Measurements |
Qinlei Huang,
Radha Railkar |
source |
16 |
| PharmaSUG |
2019 |
SAS V9.4 MNAR statement for multiple imputations for missing not at random in longitudinal clinical trials |
Lingling Li |
source |
11 |
| SGF |
2019 |
A Selective Overview of Panel Data with Applications in SAS |
Oral Capps |
source |
26 |
| SGF |
2019 |
Introducing the BGLIMM Procedure for Bayesian Generalized Linear Mixed Models |
Amy Shi,
Fang K. Chen |
source |
20 |
| SGF |
2019 |
Joint Analysis of Failure Times and Time-Varying Covariates |
Joseph C. Gardiner |
source |
22 |
| SGF |
2019 |
Review and Comparing (Analyzing) Relationship between Teacher Judgment and Student Performance in North Carolina |
Sareh Meshkinfam,
Julie S. Ivy,
Amy C. Reamer |
source |
15 |
| SGF |
2019 |
Statistical Data Checks to Identify Questionable and Suspicious Data |
Kaitie Lawson |
source |
11 |
| SGF |
2019 |
Using SAS Procedures to Fit Rasch Models |
Tianshu Pan,
Yumin Chen |
source |
10 |
| 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 |
Computer Karma: Non-Monetary Benefits from Statistical And Information Technology Volunteer Work |
Brandy R. Sinco |
|
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 |
"Training Wheels" for learning mixed models |
YuTing Tian,
Russell M. Lavery |
source |
20 |
| WUSS |
2018 |
How sensitive is your analysis? A case study on addressing it at ADaM level. |
Bhargav Koduru,
Balavenkata Pitchuka |
source |
7 |
| WUSS |
2018 |
Modeling Heterogeneous Within-Subject Variability |
Madeline Craft,
Shelley A. Blozis |
source |
8 |
| WUSS |
2018 |
Oops, I D-I-D It Again! Advanced Difference-in-Differences Models in SAS |
Margaret Warton,
Melissa Parker |
source |
17 |
| WUSS |
2018 |
When the Mean Isn't Enough: Methods for Assessing Individual Differences using SAS |
Melissa McTernan |
source |
8 |
| PharmaSUG |
2018 |
Manipulating Statistical and Other Procedure Output to Get the Results That You Need |
Vincent DelGobbo |
source |
37 |
| SGF |
2018 |
Estimation of Correlation Coefficient in Data with Repeated Measures |
Katherine Irimata,
Paul Wakim,
Xiaobai Li |
source |
19 |
| SGF |
2018 |
Insights into Using the GLIMMIX Procedure to Model Categorical Outcomes with Random Effects |
Kathleen Kiernan |
source |
23 |
| SGF |
2018 |
Manipulating Statistical and Other Procedure Output to Get the Results That You Need |
Vincent DelGobbo |
source |
37 |
| SGF |
2018 |
Model Selection Using Information Criteria (Made Easy in SAS ) |
Wendy Christensen |
source |
12 |
| SGF |
2018 |
Model Selection with Higher-Order Interactions in SAS MIXED and GLIMMIX Procedures [presentation] |
Yin Zhang,
Nanhua Zhang |
source |
11 |
| SGF |
2018 |
Penalized Variable Selection and Quantile Regression in SAS : An Overview |
Russell M. Lavery |
source |
28 |
| 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 |
Health Technology Assessment PRO Least Squares Mean Difference Programming Techniques Using SAS |
Yirong Cao,
Siory Traoré |
source
presentation source |
11 |
| PHUSE EU |
2017 |
How to Fit Longitudinal Data with Proc MCMC |
Maud Henion |
source
presentation source |
16 |
| MWSUG |
2017 |
Using SAS to Compare Two Estimation Methods on the Same Outcome: Example from First Trimester Pregnancy Weights |
Brandy R. Sinco,
Edith Kieffer,
Kathleen Welch,
Diana Welmerink Bolton |
|
15 |
| WUSS |
2017 |
Analysis of Complex Survey Data with SAS |
Christine Wells |
source |
6 |
| 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 |
| WUSS |
2017 |
Step Up Your Statistical Practice with Today's SAS/STAT Software |
Robert N. Rodriguez |
source |
19 |
| WUSS |
2017 |
Variance Ratio Estimation Using the PRECMOD SAS Macro |
Jesse Albert Canchola,
Pari Hemyari |
source |
12 |
| PharmaSUG |
2017 |
Multiple Imputation: A Statistical Programming Story |
Christopher J. Smith,
Scott Kosten |
source |
16 |
| PharmaSUG |
2017 |
Translating Statistics into Knowledge by Examples Using SAS Graphic Procedures |
Tao Shu,
Jianfei Jiang |
source |
11 |
| SGF |
2017 |
Advanced Hierarchical Modeling with the MCMC Procedure |
Fang K. Chen,
Maura E. Stokes |
source |
21 |
| SGF |
2017 |
Analyzing Correlated Data in SAS |
Niloofar Ramezani |
source |
13 |
| 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 |
Meta-Analysis of Human Trafficking in the United States |
David J. Corliss,
Heather Hill |
source |
8 |
| SGF |
2017 |
Step Up Your Statistical Practice with Today's SAS/STAT Software |
Robert N. Rodriguez,
Phil Gibbs |
source |
19 |
| SGF |
2017 |
Using a Population Average Model to Investigate the Success of a Customer Retention Strategy |
Colleen E. McGahan |
source |
19 |
| 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 |
| SESUG |
2016 |
Analyzing non-normal data with categorical response variables |
Niloofar Ramezani,
Allameh Tabataba'i |
source |
9 |
| SESUG |
2016 |
SAS Macro for Automated Model Selection Involving PROC GLIMMIX and PROC MIXED |
Fan Pan,
Jin Liu |
source |
9 |
| PHUSE EU |
2016 |
Standard Methods for Analysis and Reporting of VAS or NRS Derived Pain Relief Response Scores |
James R. Johnson |
source
presentation source |
14 |
| MWSUG |
2016 |
An Animated Guide: Penalized variable selection techniques in SAS and Quantile Regression |
Russell M. Lavery,
Peter Flom |
|
24 |
| 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 |
| MWSUG |
2016 |
The State of Human Trafficking in the Cincinnati Metropolitan Area - a Statistical Case Study |
David J. Corliss,
Heather M. Hill |
|
8 |
| MWSUG |
2016 |
Using SAS to Generate p-Values with Monte Carlo Simulation |
Brandy R. Sinco,
Edith Kieffer,
Michael S. Spencer,
Michael Woodford,
Gloria Palmisano,
Gretchen Piatt,
Michele Heisler |
|
14 |
| WUSS |
2016 |
Fitting Threshold Models using the SAS Procedures NLIN and NLMIXED |
Todd Coffey |
source |
11 |
| WUSS |
2016 |
Fitting Your Favorite Mixed Models with PROC MCMC |
Fang K. Chen |
source |
27 |
| WUSS |
2016 |
Hierarchical Generalized Linear Models for Behavioral Health Risk-Standardized 30-Day and 90-Day Readmission Rates |
Allen Hom |
source
pptx |
20 |
| WUSS |
2016 |
How D-I-D you do that? Basic Difference-in-Differences Models in SAS |
Margaret Warton,
Melissa Parker,
Andrew Karter |
source |
11 |
| WUSS |
2016 |
How to analyze correlated and longitudinal data? |
Niloofar Ramezani |
source |
8 |
| PharmaSUG |
2016 |
Mixed Effects Models |
Yan Wang |
source |
7 |
| PharmaSUG |
2016 |
PrecMod: An Automated Precision SAS Macro for Random Effects Models |
Jesse Albert Canchola,
Pari Hemyari |
source |
15 |
| 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 |
| SGF |
2016 |
Can You Stop the Guesswork in Your Marketing Budget Allocation? Marketing Mixed Modeling Using SAS Can Help! |
Delali Agbenyegah |
source |
7 |
| SGF |
2016 |
Credit Card Interest and Transactional Income Prediction with an Account-Level Transition Panel Data Model Using SAS/STAT and SAS/ETS Software |
Denys Osipenko |
source |
20 |
| SGF |
2016 |
Exploring the Factors That Impact Injury Severity Using Hierarchical Linear Modeling (HLM) |
Pradeep Bista |
source |
9 |
| SGF |
2016 |
Fitting Multilevel Hierarchical Mixed Models Using PROC NLMIXED |
Raghavendra Kurada |
source |
15 |
| SGF |
2016 |
Fitting Your Favorite Mixed Models with PROC MCMC |
Gordon Brown,
Fang K. Chen,
Maura E. Stokes |
source |
27 |
| SGF |
2016 |
Linear State Space Models in Retail and Hospitality |
Beth Cubbage |
source |
10 |
| SGF |
2016 |
PROC GLIMMIX as a Teaching and Planning Tool for Experiment Design |
Walter W. Stroup |
source
zip |
19 |
| 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 |
Can You Stop the Guesswork in Your Marketing Budget Allocation? Marketing Mixed Modeling Using SAS Can Help! |
Delali Agbenyegah |
|
7 |
| MWSUG |
2015 |
How to Build a Hierarchical Mixed Model in SAS |
Sara Burns,
Amit Amin,
Eric Novak |
|
8 |
| MWSUG |
2015 |
Using SAS for the Longitudinal Analysis of Difference Scores |
Brandy R. Sinco,
Edith Kieffer,
Michael S. Spencer,
Gloria Palmisano,
Gretchen Piatt,
Michele Heisler |
|
14 |
| PHUSE EU |
2015 |
Facing Your Fear of the Unknown - Handling Missing Data |
Amanda Reilly |
source
presentation source |
7 |
| 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 |
ANOVA_Robust: A SAS Macro for Various Robust Approaches to Testing Mean Differences in One-Factor ANOVA Models |
Thanh V. Pham,
Eun Sook Kim,
Diep T. Nguyen,
Yan Wang,
Jeffrey D. Kromrey,
Yi-Hsin Chen |
source |
14 |
| 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 |
| SESUG |
2015 |
Can Fit Indices Yielded from the SAS GLIMMIX Procedure Select the Accurate Q-matrix? |
Yan Wang,
Yi-Hsin Chen,
Isaac Y. Li,
Chunhua Cao |
source |
8 |
| SESUG |
2015 |
MIXED_RELIABILITY: A SAS Macro for Estimating Lambda and Assessing the Trustworthiness of Random Effects in Multilevel Models |
Jason A. Schoeneberger,
Bethany A. Bell |
source |
10 |
| 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 |
Introduction to SAS Quantile Regression (PROC QuantSelect and PROC QuantReg ) |
Peter L. Flom |
source |
25 |
| WUSS |
2015 |
Pattern-Mixture Random-Effects Models for Non-Ignorable Missing Data in Longitudinal Studies |
Shelley A. Blozis,
Ricardo Villarreal |
source |
3 |
| WUSS |
2015 |
Sample Size Convergence of Denominator Degrees of Freedom Method Options in SAS PROC MIXED |
Timothy Banh |
source |
13 |
| WUSS |
2015 |
SAS/STAT 14.1: Methods for Massive, Missing, or Multifaceted Data |
Maura E. Stokes |
source |
25 |
| PharmaSUG CN |
2015 |
Clinical trials optimization: Monte Carlo Simulation modeling and SAS applications |
Ye Meng |
|
5 |
| PharmaSUG CN |
2015 |
Hands-on Tutorial for Piecewise Linear Mixed-effects Models Using SAS PROC MIXED |
Qinlei Huang |
|
15 |
| PharmaSUG CN |
2015 |
Why Statistical Analysis Plan (SAP) should be comprehensive. |
Riddhi Merchant,
Ranjith Prayankotveettil |
|
6 |
| PharmaSUG |
2015 |
Missing Data For Repeated Measures: Single Imputation VS Multiple Imputation |
Giulia Tonini,
Simona Scartoni,
Camilla Paoli,
Andrea Nizzardo,
Angela Capriati |
source |
10 |
| 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 |
"Before and After" Models in Observational Research Using Random Slopes and Intercepts |
David J. Pasta |
source |
12 |
| SGF |
2015 |
A Model Family for Hierarchical Data with Combined Normal and Conjugate Random Effects [presentation] |
Geert Molenberghs |
source |
54 |
| SGF |
2015 |
Advanced Techniques for Fitting Mixed Models Using SAS/STAT Software |
Kathleen Kiernan |
source |
18 |
| SGF |
2015 |
Functional Modeling of Longitudinal Data with the SSM Procedure |
Rajesh S. Selukar |
source
zip |
19 |
| SGF |
2015 |
How to Use SAS for GMM Logistic Regression Models for Longitudinal Data with Time-Dependent Covariates |
Katherine Cai |
source |
8 |
| 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 |
Multiple Ways to Detect Differential Item Functioning in SAS |
Yan Zhang |
source |
9 |
| 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 |
SAS/STAT 14.1: Methods for Massive, Missing, or Multifaceted Data |
Maura E. Stokes,
Bob Rodriguez |
source |
25 |
| 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 |
The Comparative Analysis of Predictive Models for Credit Limit Utilization Rate with SAS/STAT |
Denys Osipenko,
Jonathan Crook |
source |
19 |
| 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 |
Analysis of Zero Inflated Longitudinal Data Using Proc NLMIXED |
Delia C Voronca,
Leonard E Egede,
Mulugeta Gebregziabher,
Ralph H. Johnson |
source |
18 |
| SESUG |
2014 |
Analyzing Multilevel Models with the GLIMMIX Procedure |
Min Zhu |
source |
19 |
| SESUG |
2014 |
Impact of Q-matrix Misspecification on Cognitive Attribute Estimation in the Crossed Random Effects LLTM Model with the SAS GLIMMIX Procedure |
Yi-Hsin Chen |
|
11 |
| 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 |
| PHUSE EU |
2014 |
Backward Selection: Immunity Test of Covariates |
Prathamesh Athavale |
source
presentation source |
10 |
| PHUSE EU |
2014 |
Unuttered Questions of Statistical Programmers |
Aparajita Dey |
source
presentation source |
10 |
| MWSUG |
2014 |
Prediction Improvement from Geostatistical Methodology in Regression Modeling For Census Tract Data |
Robert G. Downer |
|
10 |
| MWSUG |
2014 |
Using The Delta Method With Proc Mixed To Generate Means And Confidence Intervals From A Linear Mixed Model On The Original Scale, When The Analysis Is Done On The Log Scale |
Brandy R. Sinco,
Edith Kieffer,
Michael S. Spencer |
|
11 |
| WUSS |
2014 |
Analyzing Phased Interventions with Segmented Regression and Stepped Wedge Designs |
Eric C. Wong,
Po-Han Chen,
Dorothy Hung |
source |
9 |
| WUSS |
2014 |
Options in Estimating Nonlinear Mixed Models: Quadrature points and Approximation Methods |
Nate Smith,
Shelley A. Blozis |
source |
7 |
| 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 |
| PharmaSUG |
2014 |
Quickly Organize Statistical Output for Review |
Bradford J. Danner |
source |
4 |
| SGF |
2014 |
%COVTEST: A SAS Macro for Hypothesis Testing in Linear Mixed Effects Models via Parametric Bootstrap |
Peter Ott |
source |
9 |
| SGF |
2014 |
A SAS Macro to Diagnose Influential Subjects in Longitudinal Studies |
Grant Schneider,
Randy Tobias |
source
zip |
18 |
| 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 |
Analyzing Data from Experiments in Which the Treatment Groups Have Different Hierarchical Structures |
Sharon Lohr,
Peter Schochet |
source |
12 |
| SGF |
2014 |
Analyzing Multilevel Models with the GLIMMIX Procedure |
Min Zhu |
source |
18 |
| SGF |
2014 |
Bayesian Framework in Early Phase Drug Development with SAS Examples |
Howard Liang |
source |
4 |
| SGF |
2014 |
Combining Type-III Analyses from Multiple Imputations |
Binhuan Wang,
Yixin Fang,
Man Jin |
source |
6 |
| SGF |
2014 |
Comparison of Five Analytic Techniques for Two-Group, Pre-Post Repeated Measures Designs Using SAS |
J. Madison Hyer,
Jennifer L. Waller |
source |
8 |
| SGF |
2014 |
Got Randomness? SAS for Mixed and Generalized Linear Mixed Models |
David A. Dickey |
source |
12 |
| SGF |
2014 |
Introduction to Frailty Models |
John Amrhein |
source |
9 |
| SGF |
2014 |
Modeling Loss Given Default in SAS/STAT |
Xiao Yao,
Jonathan Crook,
Galina Andreeva |
source |
9 |
| SGF |
2014 |
Parameter Estimation of Cognitive Attributes Using the Crossed Random-Effects Linear Logistic Test Model with PROC GLIMMIX |
Chunhua Cao,
Yan Wang,
Yi-Hsin Chen,
Isaac Y. Li |
source |
12 |
| SGF |
2014 |
Plotting Differences Among LS-means in Generalized Linear Models |
Robin High |
source |
14 |
| SGF |
2014 |
Power and Sample Size for MANOVA and Repeated Measures with the GLMPOWER Procedure |
John M. Castelloe |
source |
20 |
| SGF |
2014 |
SAS/STAT 13.1 Round-Up |
Bob Rodriguez,
Maura E. Stokes |
source |
25 |
| SGF |
2014 |
Using Arrays for Epidemic Modeling in SAS |
Carl Grafe |
source |
7 |
| WUSS |
2013 |
Repeated Measures ANCOVA with the MIXED and GLM Procedures: Examining an Intervention to Reduce Childhood Obesity |
Lauren Cook,
Jaimie N. Davis,
Donna Spruijt-Metz,
Nicole Gatto |
source |
6 |
| WUSS |
2013 |
User-Specified Likelihood Expressions Using NLMIXED and the GENERAL Statement |
Melissa McTernan,
Shelley A. Blozis |
source |
4 |
| 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 |
| SESUG |
2013 |
Analyzing Multiway Models with ANOM Slicing |
Peter S. Wludyka |
source |
11 |
| 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 |
Evaluating the Performance of the SAS GLIMMIX Procedure for the Dichotomous Rasch model: A Simulation Study |
Isaac Y. Li,
Yi-Hsin Chen,
Jeffrey D. Kromrey |
source |
9 |
| SESUG |
2013 |
GLIMMIX_Rasch: A SAS Macro for Fitting the Dichotomous Rasch Model |
Yi-Hsin Chen |
source |
10 |
| PHUSE EU |
2013 |
Bayesian Statistics: Concept and Bayesian Capabilities in SAS |
Mark Janssens |
source
presentation source |
15 |
| MWSUG |
2013 |
Ideas and Examples in Generalized Linear Mixed Models |
David A. Dickey |
|
12 |
| NESUG |
2013 |
Marketing and Granger Causality: Going Beyond Correlation |
Jonathan Prantner |
|
11 |
| PharmaSUG |
2013 |
Probability Based Criteria in Early Phase Drug Development |
Howard Liang |
source |
5 |
| PharmaSUG |
2013 |
Reliability Assessment of Image Data in Oncology and Psychology Studies |
Li Zhang,
David Shen,
Gary Chen |
source |
7 |
| 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 Applying Multiple Imputation to Multilevel Data |
Stephen Mistler |
source |
8 |
| 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 |
| SGF |
2013 |
Predicting Health Care Expenditures with the MCMC Procedure |
Gregory Watson |
source |
12 |
| SGF |
2013 |
The Value of Neighborhood Information in Prospect Selection Models: Investigating the Optimal Level of Granularity |
Dirk Van den Poel,
Philippe Baecke |
source |
15 |
| NESUG |
2012 |
A Model for Extreme Stacking of Data at Endpoints of a Distribution |
Robert J. Gallop |
|
8 |
| NESUG |
2012 |
Building a Predictive Model for 30-Day Inpatient Readmission Using PROC PHREG |
Klaus Lemke |
|
13 |
| SCSUG |
2012 |
Use and Applications of JMP in Microbial Ecology |
Jose Garcia-Mazcorro |
source |
17 |
| SESUG |
2012 |
%MIXED_FIT: A SAS Macro to Assess Model Fit and Adequacy for Two-Level Linear Models |
Mihaela Ene |
source |
8 |
| SESUG |
2012 |
Compare MIXED and GLMMIX to Analyze Breast Cancer Longitudinal Study |
Abbas S. Tavakoli |
source |
5 |
| SESUG |
2012 |
Fitting Bayesian hierarchical multinomial logit models in PROC MCMC |
Fitting Bayesian |
source |
8 |
| SESUG |
2012 |
Random Effects Simulation for Sample Size Calculations Using SAS |
Random Effects Simulation |
source |
11 |
| 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 |
| WUSS |
2012 |
Analysis of Dietary Patterns over Freshman Year of College |
Chelsea Lofland |
source |
8 |
| WUSS |
2012 |
Sample Size Calculation and Power Analysis for Design of Experiments Using Proc Glmpower |
Chii Dean |
source |
10 |
| WUSS |
2012 |
Sensitivity analysis of nonlinear mixed-effects models for longitudinal data that areincomplete |
Shelley A. Blozis |
source |
6 |
| WUSS |
2012 |
The influence of small sample sizes on empirical Bayes' predictors inlongitudinal data sets |
Jennifer Wang |
source |
6 |
| PharmaSUG CN |
2012 |
Fitting PK Models with SAS NLMIXED Procedure (Paper, Appendix) |
Halimu Haridona |
pdf |
6 |
| PharmaSUG |
2012 |
Application of Meta-Analysis in Clinical Trials |
Marina Komaroff |
source |
7 |
| PharmaSUG |
2012 |
Computing Initial Values for Pharmacokinetic ML Nonlinear Regression via genetic algorithms and parallel genetic algorithms |
Francisco Juretig |
source |
11 |
| PharmaSUG |
2012 |
Estimating Risk in the Presence of Unreported Zeros in the Data |
Brandon Fleming |
source |
7 |
| 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 |
| PharmaSUG |
2012 |
Reporting Outliers in Data: A Macro to Identify and Report Distant Data Points |
Howard Liang,
Jason Bishop |
source |
5 |
| 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 |
Modeling Heavy-Tailed Distributions in Healthcare Utilization by Parametric and Bayesian Methods |
Joseph C. Gardiner |
source |
15 |
| SGF |
2012 |
MV_META: A SAS Macro for Multivariate Meta-Analysis |
Julie A. Gloudemans,
Corina M. Owens,
Jeffrey D. Kromrey |
source |
15 |
| SGF |
2012 |
Tips and Strategies for Mixed Modeling with SAS/STAT Procedures |
Kathleen Kiernan,
Jill Tao,
Phil Gibbs |
source |
18 |
| SGF |
2012 |
Using SAS PROC MIXED to Fit Health Policy-Based Hierarchical Models |
Lori L. Miller,
Fred Wilds |
source |
7 |
| SCSUG |
2011 |
A Simulation Study for Power Analysis in a Longitudinal Study Using SAS |
Ravi Lingineni |
source |
4 |
| SCSUG |
2011 |
Statistical comparison of relative proportions of bacterial genetic sequences |
Jose F Garcia-Mazcorro |
source |
19 |
| 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 |
| SESUG |
2011 |
On Deck: SAS/STAT 9.3 |
Maura E. Stokes,
Fang K. Chen |
source |
20 |
| SESUG |
2011 |
Proc MIXED - Right Options to get Right Output |
Shilpa C. Edupganti,
Sheetal Nisal |
source |
9 |
| WUSS |
2011 |
"Before and After" Models in Observational Research Using Random Slopes and Intercepts |
David J. Pasta |
source |
12 |
| WUSS |
2011 |
On Deck: SAS/STAT 9.3 |
Maura E. Stokes |
source |
20 |
| WUSS |
2011 |
SAS Procedure Proc Mixed to Assess the Effects of School Health Policy Requirements on Change in Student Health Outcomes |
Lori Miller |
source |
9 |
| PHUSE EU |
2011 |
Estimation of relative potency in a 4-point parallel line assay |
Stefano Vezzoli |
source
presentation source |
11 |
| 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 |
| PHUSE EU |
2011 |
Using R to Validate Results of Other Programming Environments |
Nikhil Abhyankar,
Vidyagouri Prayag |
source
presentation source |
8 |
| 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 |
| MWSUG |
2011 |
Interpreting the Differences Among LSMEANS in Generalized Linear Models |
Robin High |
|
11 |
| MWSUG |
2011 |
On Deck: SAS/STAT 9.3 |
Maura E. Stokes,
Fang K. Chen,
Ying So |
|
20 |
| MWSUG |
2011 |
PROC NLMIXED for Basic Non-Linear Regression |
Keith Dunnigan |
|
12 |
| MWSUG |
2011 |
The Effects of Previous Trial Validity on the Gaze Cuing Effect: A Meta-Analysis |
Deanna Naomi Schreiber-Gregory |
|
6 |
| NESUG |
2011 |
On Deck: SAS/STAT 9.3 |
Maura E. Stokes |
|
20 |
| NESUG |
2011 |
Proc Mixed - Right Options to Get the Right Output |
Shilpa C. Edupganti,
Sheetal Nisal |
|
10 |
| NESUG |
2011 |
SAS Macro for Nonparametric Residual Bootstrap Multilevel Modeling |
Jichuan Wang,
Peichang Shi,
Avital Cnaan |
|
6 |
| PharmaSUG |
2011 |
CONTRAST and ESTIMATE Statements Made Easy: The LSMESTIMATE Statement |
Kathleen Kiernan,
Randy Tobias,
Phil Gibbs,
Jill Tao |
source |
19 |
| PharmaSUG |
2011 |
Formulas Calculating Risk Estimates and Testing for Effect Modification and Confounding |
Manojkumar B Agravat |
source |
44 |
| PharmaSUG |
2011 |
Implementation of Pairwise Fitting Technique for Analyzing Multivariate Longitudinal Data in SAS |
Madan G. Kundu |
source |
12 |
| PharmaSUG |
2011 |
Implementation of Pattern-Mixture Models Using Standard SAS/STAT Procedures |
Bohdana Ratitch,
Michael O'Kelly |
source |
10 |
| PharmaSUG |
2011 |
Statistical Analysis of Adverse Events in Randomized Clinical Trials Using SAS |
Dongsun Cao,
Xiaomin He |
source |
12 |
| PharmaSUG |
2011 |
Using SAS for Modeling and Simulation in Drug Development - A Review and Assessment of Some Available Tools |
Melvin S. Munsaka,
Michael Carniello |
source |
10 |
| SGF |
2011 |
CONTRAST and ESTIMATE Statements Made Easy: The LSMESTIMATE Statement |
Kathleen Kiernan,
Randy Tobias,
Phil Gibbs,
Jill Tao |
source |
19 |
| SGF |
2011 |
Contrast Statements for Binary Responses: Comparing and Contrasting with PROC GLIMMIX |
Jeffrey M. Gossett,
Mary Aitken,
Beverly K. Miller,
Christopher J. Swearingen |
source |
10 |
| SGF |
2011 |
Evaluating the Effectiveness of a Calcium Nutrition Educational Intervention for Middle School Students in Las Vegas, Nevada, Using SAS |
Ryan Fernandez |
source |
13 |
| 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 |
Rasch Model and Beyond with PROC GLIMMIX: A Better Choice |
Teck Kiang Tan,
Wenshu Luo,
David Hogan |
source |
12 |
| SGF |
2011 |
Repeated Measures Analysis of Correlated Data with Multiple Responses Using SAS |
Anbuchelvi Jeyabslasingham,
Anpalaki J. Ragavan |
source |
10 |
| SGF |
2011 |
Small Area Estimation for Survey Data Analysis Using SAS Software |
Pushpal K. Mukhopadhyay,
Allen McDowell |
source |
19 |
| SGF |
2011 |
Statistical Modeling of Surface Complexation of Selenium onto Iron and Aluminum Oxides using SAS |
Anpalaki J. Ragavan |
source |
13 |
| SGF |
2011 |
The RANDOM Statement and More: Moving On with PROC MCMC |
Fang K. Chen |
source |
21 |
| NESUG |
2010 |
The Next Generation: SAS/STAT 9.22 |
Maura E. Stokes,
Robert N. Rodriguez,
Robert Cohen |
|
20 |
| SCSUG |
2010 |
How Good is Your School |
Steve Fleming |
source |
16 |
| WUSS |
2010 |
Evaluating the Effectiveness of a Calcium Nutrition Educational Intervention for Middle School Students in Nevada using SAS |
Ryan Fernandez |
source |
14 |
| WUSS |
2010 |
Logit-based Neutral Zone Classification Algorithm with Application to Microbial Community Profiling |
Rebecca Le |
source |
9 |
| WUSS |
2010 |
Mathematical Programming for Surface Complexation Modeling Using SAS |
Anpalaki J. Ragavan |
source |
13 |
| WUSS |
2010 |
The Next Generation: SAS/STAT 9.22 |
Robert N. Rodriguez |
source |
20 |
| PHUSE EU |
2010 |
Uncover Useful Patterns in Clinical Trials Safety Data with JMP Clinical |
Valérie Nedbal |
source |
7 |
| PHUSE EU |
2010 |
Useful Tips for Analysis of Variance (ANOVA) in Multicentre, Placebo Controlled Clinical Trials |
Joanna Romaniuk |
source
presentation source |
12 |
| 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 |
Technical Resources for Beginning SAS Programmers |
Brian K. Varney |
|
7 |
| MWSUG |
2010 |
The Next Generation: SAS/STAT 9.22 |
Maura E. Stokes |
|
20 |
| MWSUG |
2010 |
Using HPMIXED and Other SAS Procedures to Efficiently Analyze Large Dimension Registry Data |
Matthew Fenchel,
Gary McPhail,
Rhonda D. VanDyke |
|
19 |
| SESUG |
2010 |
Fitting multivariate random-effects models using SAS PROC GLIMMIX |
Lei Li,
Namasivavayam Ambalavanan,
Abhik Das |
source |
8 |
| PharmaSUG |
2010 |
Dynamic Determination of Mixed Model Covariance Structures in Double-blind Clinical Trials |
Matthew Davis |
|
7 |
| PharmaSUG |
2010 |
Linear Mixed Models in Clinical Trials using PROC MIXED |
Danyang Bing,
Xiaomin He |
|
12 |
| PharmaSUG |
2010 |
Two-piecewise Random Coefficient Model Using Proc Mixed |
Shengjie Wu |
|
6 |
| SGF |
2010 |
A Grad Student 'How-To' Paper on Grant Preparation: Preliminary Data, Power Analysis, and Presentation |
Elisa L. Priest,
Derek Blankenship |
source |
14 |
| SGF |
2010 |
Building Latent Growth Models Using PROC CALIS: A Structural Equation Modeling Approach |
Teck Kiang Tan,
Trivina Kang,
David Hogan |
source |
19 |
| 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 |
Fundamental Diagnostics for Two-Level Mixed Models: The SAS Macro MIXED_DX |
Bethany A. Bell,
Jason A. Schoeneberger,
Grant B. Morgan,
Jeffrey D. Kromrey,
John M. Ferron |
source |
12 |
| SGF |
2010 |
Ideas and Examples in Generalized Linear Mixed Models |
David A. Dickey |
source |
12 |
| SGF |
2010 |
Practicalities of Using ESTIMATE and CONTRAST Statements |
David J. Pasta |
source |
20 |
| 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 |
| SGF |
2010 |
Using the NLMIXED Procedure to Fit Linear and Nonlinear Growth Curve Models |
Mo Zheng |
source |
6 |
| SESUG |
2009 |
A New Effect Modification P Value Test Demonstrated |
Manojkumar B Agravat |
source |
14 |
| SESUG |
2009 |
MIXED_DX: A SAS Macro for Two-Level Linear Model Diagnostics |
Bethany A. Bell,
Grant B. Morgan,
Jason A. Schoeneberger,
John M. Ferron,
Jeffrey D. Kromrey |
source |
17 |
| 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 |
| SESUG |
2009 |
Streamlining Data Analysis |
Edzard van Santen |
source |
4 |
| SESUG |
2009 |
The Effect of Missing Data on Repeated Measures Models |
Maribeth H. Johnson |
source |
10 |
| MWSUG |
2009 |
Mixed Model Selection |
George C. J. Fernandez |
|
19 |
| PNWSUG |
2009 |
The 7 Habits of Highly Effective SAS-ers |
David L. Cassell |
|
17 |
| PNWSUG |
2009 |
Wait Wait, Don't Tell Me… You're Using the Wrong Proc! |
David L. Cassell |
|
11 |
| NESUG |
2009 |
Build Multilevel Model to Assess the Length to Inpatient Readmission Using SAS PROC MIXED |
Qingfeng Liang |
|
13 |
| WUSS |
2009 |
A Beginner's Example of PROC MIXED for the Analysis of Letter Identification Using Reaction Time |
Sarah R. Greene |
source |
4 |
| WUSS |
2009 |
A Biometric Analysis of Twin Data Using PROC MIXED |
Mo Zheng |
source |
8 |
| WUSS |
2009 |
Evaluating the Change in Lung Function Over Time: Practicalities of Using ESTIMATE and CONTRAST Statements |
David J. Pasta |
source |
13 |
| PharmaSUG |
2009 |
Concepts and Ideas for Developing and Maintaining a Utility Toolbox of SAS Statistical Procedures |
David W. Carr |
|
6 |
| PharmaSUG |
2009 |
Modeling the Treatment Effect on a Median of a Percent Change from Baseline in a Log-normal Variable Using SAS PROC NLMIXED |
Aiming Yang |
|
5 |
| SGF |
2009 |
A SAS Macro for Adaptive Regression Modeling |
George J. Knafl |
source |
9 |
| SGF |
2009 |
All the Cows in Canada: Massive Mixed Modeling with the HPMIXED Procedure in SAS 9.2 |
Tianlin Wang |
source |
15 |
| SGF |
2009 |
Analysis of Survival Data with Clustered Events |
Lida Gharibvand,
Lei Liu |
source |
11 |
| 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 |
| 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 |
Creating county-level estimates from National Weather Service data |
Liang Wei |
source |
14 |
| SESUG |
2008 |
Marketing Mix Modeling: Techniques and Challenges |
Patralekha Bhattacharya |
source |
6 |
| SESUG |
2008 |
Non Linear Programming Of Time Series Data To Minimize Eutrophication In Truckee River, Nevada |
Anpalaki J. Ragavan |
source |
13 |
| 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 |
Concepts and Ideas for Developing and Maintaining a Utility Toolbox of SAS Statistical Procedures |
David W. Carr |
source |
6 |
| PHUSE EU |
2008 |
Statistics for Non-Statisticians |
Shambhavi Nayak |
source |
10 |
| PNWSUG |
2008 |
Wait Wait, Don't Tell Me… You're Using the Wrong Proc! |
David L. Cassell |
|
11 |
| NESUG |
2008 |
Analysis of Correlated Recurrent and Terminal Events Data in SAS |
Li Lu,
Chenwei Liu |
|
8 |
| 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 |
| NESUG |
2008 |
SAS Program for Bivariate Growth Curve with Kalman Filter |
Amy E. Begley,
Qianyu Dang,
Patricia R. Houck,
Sati Mazumdar |
|
6 |
| PharmaSUG |
2008 |
Bayesian Data Analysis Using %WinBUGS |
Lei Zhang |
|
18 |
| PharmaSUG |
2008 |
Sample Size Estimation Through Simulation of a Random Coefficient Model by Using SAS |
Junliang Chen,
Shannon Stock,
Chunqin Deng |
|
8 |
| SGF |
2008 |
Applying SAS Mixed-Model Procedures to Educational-Assessment Data |
Brian Patterson |
source |
8 |
| 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 |
Data Mining Application of Non-Linear Mixed Modeling in Water Quality Analysis |
Anpalaki J. Ragavan |
source |
14 |
| 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 |
| NESUG |
2007 |
A SAS Macro to Automate the Process of Pooling Sites |
Changhong Shi,
Lili Chen |
|
6 |
| NESUG |
2007 |
Nonlinear Programming for Maximum Likelihood Estimation |
Robert J. Gallop |
|
12 |
| SESUG |
2007 |
A SAS Macro to Automate the Process of Pooling Sites |
Changhong Shi |
source |
6 |
| SESUG |
2007 |
PROC MIXED: Underlying Ideas with Examples |
David A. Dickey |
source |
19 |
| 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 |
| WUSS |
2007 |
Wait Wait, Don't Tell Me… You're Using the Wrong Proc! |
David L. Cassell |
source |
11 |
| PHUSE EU |
2007 |
A gentle introduction to Meta-analysis |
Angelo Tinazzi,
Jayne Tierney |
source |
8 |
| 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 |
| PNWSUG |
2007 |
An Introduction to Statistical Power Calculations for Linear Models with SAS 9.1 |
Robin High |
|
17 |
| PharmaSUG |
2007 |
Effects of Multicollinearity in All Possible Mixed Model Selection |
George C. J. Fernandez |
|
18 |
| PharmaSUG |
2007 |
Growing Growth Curves Using PROC MIXED and PROC NLMIXED |
Jeffrey M. Gossett,
Pippa Simpson,
Patrick Casey,
Leanne Whiteside-Mansell,
Robert Bradley,
Chan-Hee Jo |
|
10 |
| PharmaSUG |
2007 |
SAS Markov Chain Monte Carlo (MCMC) Simulation in Practice |
Shi-Tao Yeh,
Scott D Patterson |
|
20 |
| SGF |
2007 |
Attitudes toward Immigrants and Immigration in the United States: Toward a Structural Approach |
Michael J. Sobczak |
source |
12 |
| 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 |
Graphing Longitudinal Data: Deaf Children in the "Children of the National Longitudinal Survey of Youth" |
Paul Dirmyer,
Richard Schley,
Sara Martino |
source |
10 |
| SGF |
2007 |
Growing Up Fast: SAS 9.2 Enhancements to the GLIMMIX Procedure |
Oliver Schabenberger |
source |
20 |
| SGF |
2007 |
Marginal Interpretation of Subject-Specific Curves: Logistic-Normal Regression |
Pedro A. Macchiavelli,
Raul Torres |
source |
10 |
| 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 |
| SGF |
2007 |
Split and Conquer! Using SAS/QC to Design Quality into Complex Manufacturing Processes |
Jose G. Tobias,
Randall D. Ramirez |
source |
25 |
| SGF |
2007 |
Using PROC NLMIXED and PROC GLMMIX to Analyze Dyadic Data with a Dichotomous Dependent Variable |
Peter L. McMahon,
James M. Pouget,
Enrique R. Flom |
source |
10 |
| SGF |
2007 |
Using SAS PROC NLMIXED for Robust Regression |
Steven A. Chen,
Lingyun Gilbert |
source |
9 |
| PNWSUG |
2006 |
Wait Wait, Don't Tell Me… You're Using the Wrong Proc! |
David L. Cassell |
|
11 |
| PNWSUG |
2006 |
You Can't Stop Statistics: SAS/STAT Software Keeps Rolling Along |
Maura E. Stokes,
Robert N. Rodriguez |
|
32 |
| MWSUG |
2006 |
All Possible Model Selection in Proc Mixed - A SAS macro application |
George C. J. Fernandez |
|
19 |
| PHUSE EU |
2006 |
Adding (p-) Value to Tables -- a Programmer''s Perspective |
Kathryn Wright |
source |
10 |
| PHUSE EU |
2006 |
Analysis of incomplete two-period crossover trials with SAS PROC MIXED |
Jochen Müller-Cohrs |
source |
8 |
| PHUSE EU |
2006 |
Proc mixed -- Trials and Tribulations |
Shelley Fordred |
source |
7 |
| PHUSE EU |
2006 |
Statistics and Pharmacokinetics in Clinical Pharmacology Studies |
Amy Newlands |
source |
8 |
| SESUG |
2006 |
Comparing Time series, Generalized Linear Models and Artificial Neural Network Models for Transactional Data Analysis |
Joseph Twagilimana |
source |
9 |
| SESUG |
2006 |
Graphics for Statistical Concepts and Data Display |
David A. Dickey |
source |
19 |
| 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 |
| SESUG |
2006 |
PO04 PUB_BIAS: A SAS Macro for Detecting |
Publication Bias,
Gianna Rendina-Gobioff,
Jeffrey D. Kromrey |
source |
17 |
| SESUG |
2006 |
Predictive Modeling to Analyze Hospital Charges Versus Reimbursements |
Chakib Battioui |
source |
12 |
| WUSS |
2006 |
Hierarchical Logistic Regression Modeling with SAS GLIMMIX |
Jian Dai,
Zhongmin Li,
David Rocke |
source |
9 |
| WUSS |
2006 |
Mixed Model Selection via the Information-Theoretic Approch using SAS |
Jesse Albert Canchola,
Torsten B. Neilands |
source |
7 |
| 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 |
| WUSS |
2006 |
Wait Wait, Don't Tell Me… You're Using the Wrong Proc! |
David L. Cassell |
source |
11 |
| NESUG |
2006 |
Statistical analysis of clustered data using SAS |
Gui-Shuang Ying,
Chengcheng Liu |
|
13 |
| NESUG |
2006 |
Using PROC NLMIXED and PROC GLIMMIX to analyze dyadic data with binary outcomes |
Peter L. Flom,
Samuel Friedman,
James McMahon,
Enrique Pouget |
|
10 |
| NESUG |
2006 |
Using SAS to Find Bootstrap Estimates of Field Air Sampling Data |
James Slaven,
David Bartley,
Mike Rose,
Martin Harper,
Michael Andrew |
|
4 |
| NESUG |
2006 |
You Can't Stop Statistics |
Maura E. Stokes,
Robert N. Rodriguez |
|
32 |
| 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 |
| PharmaSUG |
2006 |
Data Mining Methods to Link Multiple Drug Purchases and To Investigate Drug Costs to Consumers |
Patricia B. Cerrito |
|
15 |
| 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 |
Analysis of Large Hierarchical Data with Multilevel Logistic Modeling Using PROC GLIMMIX |
Jia Li,
Toni Alterman,
James A. Deddens |
source |
5 |
| SUGI |
2006 |
Analyzing Multivariate Longitudinal Data Using SAS |
Feng Gao,
Chengjie Xiong,
Paul A. Thompson,
J. Philip Miller |
source |
9 |
| 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 |
Empirical Power Estimation for Phase I Dose-Proportionality Studies Based on Power-Law Model Using Confidence Interval Criteria |
Jihao Zhou,
Jane Li,
Bruce Coate,
Melissa Chen |
source |
11 |
| 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 |
| SUGI |
2006 |
Using SAS to Investigate Effect Modification |
Peter H. Van Ness,
Heather G. Allore |
source |
10 |
| SUGI |
2006 |
Wait Wait, Don't Tell Me… You're Using the Wrong Proc! |
David L. Cassell |
source |
11 |
| SUGI |
2006 |
You Can't Stop Statistics |
Maura E. Stokes,
Robert N. Rodriguez |
source |
32 |
| PNWSUG |
2005 |
Assessing Within- and Between-Subject Effects with Correlated Clinical Data |
Marla J. Husnik,
Eugene Huang,
Grant Colfax |
|
10 |
| SESUG |
2005 |
An Introduction to ODS for Statistical Graphics in SAS 9.1 |
Robert N. Rodriguez |
source |
27 |
| 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 |
| MWSUG |
2005 |
Relationship Between Total Charges And Reimbursements In Outpatient Visits Using SAS GLMMIX |
Chakib Battioui |
|
6 |
| 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 |
| 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 |
Adopting New Techniques: Statistical Procedures to Determine the Agreement between two Laboratory Methods |
Ashley Peterson,
Larry W. Douglass |
|
13 |
| NESUG |
2005 |
Algorithm and Software for Yield Analysis |
Igor Mandel,
Victor Kamensky |
|
16 |
| NESUG |
2005 |
Introducing the GLIMMIX Procedure for Generalized Linear Mixed Models |
Oliver Schabenberger |
|
20 |
| PharmaSUG |
2005 |
An Introduction to ODS for Statistical Graphics in SAS 9.1 |
Robert N. Rodriguez |
|
27 |
| PharmaSUG |
2005 |
Assessing Within- and Between-Subject Effects with Correlated Clinical Data |
Marla J. Husnik,
Eugene Huang,
Grant Colfax |
|
10 |
| 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 |
Analyzing Incomplete Binary Repeated Measures Data Using SAS |
Bin Yang |
source |
8 |
| SUGI |
2005 |
Empirical Power for Higher-Order Crossover Designs in Comparative Bioavailability Clinical Trials |
Jihao Zhou,
Bruce Coate |
source |
10 |
| 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 |
| SUGI |
2005 |
Using SAS to Estimate Proportional Odds Ratio Model for Meta-Analysis of Diagnostic Tests |
Mir S. Siadaty,
Jianfen Shu |
source |
10 |
| NESUG |
2004 |
An Introduction to ODS for Statistical Graphics in SAS 9.1 |
Maura E. Stokes |
|
27 |
| NESUG |
2004 |
Progress in SAS Scientific Discovery Solutions: Genetics, Microarrays, and Proteomics |
Russell D. Wolfinger,
Wendy Czika,
Kristen Kleiss |
|
18 |
| SESUG |
2004 |
Crossover Designs and Proc Mixed In SAS |
Hossein N. Yarandi |
source |
11 |
| SESUG |
2004 |
Mixed Model Influence Diagnostics |
Oliver Schabenberger |
source |
17 |
| SESUG |
2004 |
Spatial Statistics Using the SAS Bridge for ESRI |
Patricia B. Cerrito,
Carol Hanchette,
William Dakan,
George R. Barnes,
Robert Forbes |
source |
15 |
| WUSS |
2004 |
An Introduction to ODS for Statistical Graphics in SAS 9.1 |
Robert N. Rodriguez |
source |
27 |
| WUSS |
2004 |
Mixed Model Influence Diagnostics |
Oliver Schabenberger |
source |
17 |
| 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 |
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 |
Incremental Methods of Imputation for Longitudinal Data with Informative Missingness |
Naum M. Khutoryansky |
|
4 |
| 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 |
Progress in SAS Scientific Discovery Solutions: Genetics, Microarrays, and Proteomics |
Russell D. Wolfinger,
Wendy Czika,
Kristen Kleiss |
|
18 |
| PharmaSUG |
2004 |
SAS Application in 2x2 Crossover Clinical Trial |
Wuwei Wayne Feng |
|
10 |
| PharmaSUG |
2004 |
Statistical Application of SAS in Method Comparison Analysis |
David Shen |
|
13 |
| PharmaSUG |
2004 |
The Analysis of Gene Markers and the Use of SAS Procedures to Examine MicroArray Data |
Patricia B. Cerrito |
|
14 |
| PharmaSUG |
2004 |
The Meta-Analysis (PROC MIXED) of Two Pilot Clinical Studies with a Novel Antidepressant |
Lev Sverdlov,
Park Ridge |
|
6 |
| PharmaSUG |
2004 |
The Paired T-Test: Does PROC MIXED Produce the Same Results as PROC TTEST? |
Jack S. Nyberg |
|
5 |
| PharmaSUG |
2004 |
Traditional Repeated Measures Analysis Versus Random Coefficients Models Using PROC MIXED |
Radhi Abdulnabi |
|
9 |
| SUGI |
2004 |
An Introduction to ODS for Statistical Graphics in SAS 9.1 |
Robert N. Rodriguez |
source |
28 |
| SUGI |
2004 |
Bayesian Model Averaging Using SAS Software |
Melissa Whitney,
Ngo Long |
source |
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 |
Mixed Model Influence Diagnostics |
Oliver Schabenberger |
source |
18 |
| SUGI |
2004 |
On the Use of PROC MIXED to Estimate Correlation in the Presence of Repeated Measures |
Anthony C. Hamlett,
Louise Ryan,
Russell D. Wolfinger |
source |
8 |
| SUGI |
2004 |
Progress in SAS Scientific Discovery Solutions: Genetics, Microarrays, and Proteomics |
Russell D. Wolfinger,
Wendy Czika,
Kristen Kleiss |
source |
19 |
| SUGI |
2004 |
Repeated Measures Modeling with PROC MIXED |
E. Barry Moser |
source |
20 |
| SUGI |
2004 |
Successfully Supporting SAS at the University: Lessons Learned |
David C. Steven |
source |
9 |
| SUGI |
2004 |
Widefiles, Deepfiles, and the Fine Art of Macro Avoidance |
Howard L. Kaplan |
source |
11 |
| WUSS |
2003 |
How to Get a Graph from a Complex Linear Model |
Stefanie J. Silva |
source |
4 |
| WUSS |
2003 |
Presenting Logistic Regression Models to Non-Statisticians: Adjusted Probabilities and Adjusted Risk Ratios |
David J. Pasta,
Miriam G. Cisternas |
source |
4 |
| SESUG |
2003 |
An Introduction to Genomics and SAS Scientific Discovery Solutions |
Russell D. Wolfinger |
source |
7 |
| SESUG |
2003 |
Comparison of PROC MIXED and PROC GLM for Analysis of Repeated Measures Data |
Hossein N. Yarandi |
source |
6 |
| SESUG |
2003 |
Statistical Analysis of Genotype X Environment Interaction in Agricultural Research |
K. Bondari |
source |
6 |
| NESUG |
2003 |
Using ODS |
Ban Cheah |
|
17 |
| 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 |
| PharmaSUG |
2003 |
Using SAS software for Multilevel Models in Survival Analysis |
Gisela Tunes da Silva |
|
4 |
| SUGI |
2003 |
An Introduction to Genomics and SAS Scientific Discovery Solutions |
Russell D. Wolfinger,
Susan Flood |
source |
7 |
| SUGI |
2003 |
An Introduction to the Analysis of Mixed Models |
Dallas E. Johnson |
source |
4 |
| SUGI |
2003 |
Developing Client/Server Applications to Maximize SAS 9 Parallel Capabilities |
Cheryl Doninger |
source |
10 |
| SUGI |
2003 |
Estimating Standard Errors for CLASS Variables in Generalized Linear Models Using PROC IML |
David J. Pasta,
Miriam G. Cisternas |
source |
6 |
| SUGI |
2003 |
Multilevel Designs and Their Analyses |
George A. Milliken |
source |
|
| SUGI |
2003 |
Randomized Rounding |
Erik W. Tilanus |
source |
2 |
| SUGI |
2003 |
Smoothing with SAS PROC MIXED |
Alexander Pedan |
source |
5 |
| MWSUG |
2002 |
Random Coefficient Model for Hazard Analysis Critical Control Points (HACCP) A Pilot Study |
Xinpeng (Tom) Wang,
Yating Sun,
Julie Caswell |
|
3 |
| MWSUG |
2002 |
Random, Repeated or Both? Analyzing a Repeated Measures Design using PROC MIXED |
Keith Dunnigan |
|
7 |
| MWSUG |
2002 |
Using Model Fitting Information and PROC PLOT to Select the Type of Varianc-Covariance Structur |
Radhi Abdulnabi |
|
7 |
| SCSUG |
2002 |
Geostatistical Tools in the SAS System |
E. Barry Moser |
|
6 |
| NESUG |
2002 |
Estimating Confidence Intervals Around Relative Changes in Outcomes in Segmented Regression Analyses of Time Series Data |
Fang Zhang,
Anita Wagner,
Stephen B. Soumerai,
Dennis Ross-Degnan |
|
7 |
| NESUG |
2002 |
Some Analysis Methods for Behavioral Toxicology Data |
Richard R. Allen |
|
8 |
| SESUG |
2002 |
A Macro for Computing a Goodness of Fit Statistic for Linear Mixed Models |
Jean G. Orelien |
source |
5 |
| WUSS |
2002 |
Multiple Linear Regression Analysis of Total Mercury Levels in Blood and Urine Samples |
Miki Yamauchi,
George C. J. Fernandez,
Stanley Omaye |
source |
6 |
| PharmaSUG |
2002 |
Bayesian Analysis of Population Bioequivalence Using the Independence Chain Algorithm in PROC MIXED |
Chain Algorithm |
|
6 |
| PharmaSUG |
2002 |
Two Step Approach to Automatically Generate ESTIMATE Statements for Pair-wise Treatment Comparisons |
Eric Qi,
Guanghan (Frank) Liu |
|
4 |
| 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 |
A SAS/IML Macro for Computation of Confidence Intervals for Variance Components of Mixed Models |
Ann M. Hess,
Hari Iyer |
source |
4 |
| SUGI |
2002 |
How to Use SAS for Logistic Regression with Correlated Data |
Oliver Kuss |
source |
5 |
| SUGI |
2002 |
Individual Growth Analysis Using PROC MIXED |
Maribeth H. Johnson |
source |
7 |
| SUGI |
2002 |
SAS Tools for Meta-analysis |
Robert M. Hamer,
Pippa M. Simpson |
source |
6 |
| MWSUG |
2001 |
Using The SAS Mixed Procedure to Analyze the Repeated Measures Data |
Hongsen Zhou |
|
9 |
| NESUG |
2001 |
Leaping Nodes in a Single Bound: Supporting SAS MP CONNECT with Windows 2000 Advanced Server |
Carol A. Murphree |
|
5 |
| 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 |
| VIEWS |
2001 |
The Version 8 Applied Statistician |
David Shannon |
|
15 |
| 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 |
Nonlinear Least Squares Analysis of HIV Viral Load Data - Aids in Parameter Estimation |
Peter P. Gaccione |
|
8 |
| PharmaSUG |
2001 |
Power and Sample Size Determination for Linear Models |
John M. Castelloe |
|
14 |
| SUGI |
2001 |
A Macro Program for ANOVA or ANCOVA, Using PROC GLM or PROC MIXED |
Zaizai Lu,
David Shen |
source |
4 |
| SUGI |
2001 |
Analysis of Count Data Using SAS |
Alexander Pedan |
source |
6 |
| SUGI |
2001 |
Approximations to Distributions of Test Statistics in Complex Mixed Linear Models Using SAS PROC MIXED |
G. Bruce Schaalje |
source |
6 |
| SUGI |
2001 |
Model Fitting in PROC GENMOD |
Jean G. Orelien |
source |
6 |
| SUGI |
2001 |
New Methods for Modeling Reliability Using Degradation Data |
Jose G. Ramirez,
Gordon Johnston |
source |
7 |
| 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 |
| SCSUG |
2000 |
Repeated-Measures Analysis and PROC MIXED |
Shana Smith,
Torsten B. Neilands |
|
17 |
| SCSUG |
2000 |
The Use of PROC MIXED for Analyzing Cohort-Sequential Designs |
C. Nathan Marti |
|
11 |
| SESUG |
2000 |
Computation of pvalues for Multiple Comparisons with a Control in the SAS System |
Jean G. Orelien |
source |
9 |
| NESUG |
2000 |
A Pragmatic Intent-to-Treat Analysis Using SAS |
Patricia R. Houck,
Sati Mazumdar,
Kenneth S. Liu,
Charles F. Reynolds III |
|
5 |
| WUSS |
2000 |
Monkey Games: Analysis of Some Behavioral Toxicology Data |
Richard R. Allen |
source |
7 |
| 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 |
| PharmaSUG |
2000 |
Running Reports Using the PROC Mixed Procedure |
Marina V. Kungurtseva |
|
8 |
| SUGI |
2000 |
Analysis of Environmental Data Using JMP |
Andy Mauromoustakos |
source |
6 |
| 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 |
| SUGI |
2000 |
Modeling Longitudinal Growth Data and Growth Percentiles with Polynomial Gompertz Model in SAS Software |
Inna Perevozskaya,
Olga M. Kuznetsova |
source |
6 |
| SESUG |
1999 |
Analysis of Longitudinal Data: Comparison between PROC GLM and PROC MIXED |
Maribeth H. Johnson |
source |
6 |
| WUSS |
1999 |
A SAS Macro for Hierarchical Data Simulation |
Weimin (Wiliiam) Sun,
Chih-Ping Chou |
source |
6 |
| WUSS |
1999 |
Exploring Enzyme-Linked Immunosorbent Assay (ELISA) Data with the SAS Analyst Application |
Stewart L. Fossceco,
Nathan A. Curtis |
source |
9 |
| WUSS |
1999 |
Minimizing Mixed Output |
Stefanie J. Silva,
Dave P. Miller |
source |
4 |
| WUSS |
1999 |
Quantifying Regression to the Mean Using PROC MIXED |
Thaddeus J. Haight,
Long Ngo,
Ira Tager |
source |
6 |
| WUSS |
1999 |
Study of Genotype x Environmental Interaction Effects - Using SAS MACROs for AMMI and Tai's Stability models |
Mathura Tillainathan,
George C. J. Fernandez |
source |
6 |
| NESUG |
1999 |
Fitting Nonlinear Mixed Models with the New NLMIXED Procedure |
Russell D. Wolfinger |
|
10 |
| NESUG |
1999 |
Get Report Running PROC Mixed Procedure |
Marina V. Kungurtseva |
|
10 |
| MWSUG |
1999 |
A General Gibbs Sampling Algorithm for Analyzing Linear Models Using the SAS System |
Jayawant N. Mandrekar,
Daniel J. Sargent,
Paul J. Novotny,
Jeff A. Sloan |
|
6 |
| MWSUG |
1999 |
Longitudinal Data Analysis Repeated-Measure ANOVA and Mixed Models |
Nancy E. Briggs,
Ching-Fan Sheu |
|
6 |
| MWSUG |
1999 |
Sample Size Determination From A Pilot Bioequivalence Study For A Future Pivotal Bioequivalence Study: A SAS Procedure |
Xiang Gao,
Henry Cheng |
|
7 |
| 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 |
A General Gibbs Sampling Algorithm for Analyzing Linear Models Using the SAS System |
Daniel J. Sargent,
Jayawant N. Mandrekar,
Paul J. Novotny,
Jeff A. Sloan |
source |
|
| 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 |
| SUGI |
1999 |
Fitting Nonlinear Mixed Models with the New NLMIXED Procedure |
Russell D. Wolfinger |
source |
10 |
| SUGI |
1999 |
The Effect of Missing Data on Repeated Measures Models |
Maribeth H. Johnson |
source |
6 |
| SUGI |
1999 |
Using the Mixed Procedure to Analyze a Fractional Factorial Split-Plot Experiment |
Jon M. Lindenauer |
source |
4 |
| MWSUG |
1998 |
Using PROC MIXED To Analyze a Repeated Measures Design |
Keith Dunnigan |
|
6 |
| WUSS |
1998 |
Estimating Standard Errors of Treatment Effects for Probit Models and for Linear Models of Log-Transformed Variables with PROC IML |
David J. Pasta,
Miriam Cisternas,
Cynthia L. Williamson |
source |
6 |
| NESUG |
1998 |
Macro for computing LOCF: Comparison of results with PROC MIXED |
Patricia R. Houck |
|
2 |
| SESUG |
1998 |
The Effect of Missing Data on Repeated Measures Models |
Maribeth H. Johnson |
|
5 |
| SEUGI |
1998 |
GLM and MIXED procedures to treat longitudinal data |
Sandrine Laguerre |
source |
9 |
| SEUGI |
1998 |
Time to market reduction: A methodological approach to the virual prototyping of stamped component |
F. Placidi,
Franca Vicino,
S. Martire |
source |
13 |
| SEUGI |
1998 |
Use of the SAS VARCOMP Procedure to estimate analytical repeatability |
Anna Carroli |
source |
5 |
| SUGI |
1998 |
A Macro for Converting Mean Separation Output to Letter Groupings in PROC MIXED |
Arnold M. Saxton |
source |
4 |
| SUGI |
1998 |
An Introduction to the Analysis of Repeated Measures for Continuous Response Data using PROC GLM and PROC MIXED |
Robert M. Hamer,
Pippa M. Simpson |
source |
4 |
| SUGI |
1998 |
Multivariate Analysis Using the MIXED Procedure |
S. Paul Wright |
source |
5 |
| SUGI |
1998 |
Nonlinear Mixed Effects Models, a Tool for Analyzing Repeated Measurements: A Brief Tutorial Using SAS Software |
Peter P. Gaccione,
M.S. Blanchard |
source |
6 |
| SUGI |
1998 |
Overall Part Number Item |
Rank Rank |
source |
19 |
| SUGI |
1998 |
Statistical Development Using SAS/TOOLKIT Software |
Scott D. Grimshaw,
Gilbert W. Fellingham |
source |
4 |
| SUGI |
1998 |
The Effect of Missing Data on Sample Sizes for Repeated Measures Models |
Maribeth H. Johnson,
Peter P. Davis |
source |
5 |
| WUSS |
1997 |
Cross-Validation Estimates of the Prediction Error in a Random-Coefficients Mixed Model Used to Estimate Emissions from On-Road Motor Vehicles using SAS |
Steven Brisby |
source |
5 |
| WUSS |
1997 |
Estimation of Shelf-Life and the Minimum Effective Dose Using PROC MIXED |
Louis Munyakazi |
source |
6 |
| NESUG |
1997 |
Nonlinear Mixed Effects Models, a tool for analyzing repeated-measurements data whose function is nonlinear in the parameters. |
Suzette Blanchard |
|
7 |
| MWSUG |
1997 |
Using SAS/STAT to Analyze Correlated Data |
Marlene Goormastic |
|
7 |
| SESUG |
1997 |
Analysis of Repeated Measures and Longitudinal Data |
Jane Pendergast |
|
8 |
| SESUG |
1997 |
The Case of the Missing Data |
Maribeth H. Johnson,
Mark S. Litaker |
|
6 |
| SEUGI |
1997 |
Analysing the incidence of Leukaemia in England and Wales |
David Rowland,
Deborah Allon,
Paul Nicholson,
Richard McNally |
source |
9 |
| SEUGI |
1997 |
Inter-rater agreement in medical studies: analysis tools within SAS software |
Barbara G. Schneider |
source |
12 |
| 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 |
Characterization of Variance in Medical Diagnostics: The Analysis of "Usual" Data |
John A. Wass |
source |
5 |
| SUGI |
1997 |
Estimation via EM-Algorithm in a Bivariate Random Effects Model |
Amrik Shah,
Kirk A. Easley |
source |
8 |
| SUGI |
1997 |
Model Selection in Linear Mixed Effects Models Using SAS PROC MIXED |
Long Ngo,
Richard Brand |
source |
6 |
| SUGI |
1997 |
SAS/INSIGHT Software or JMP Software: A Comparison |
Andy Mauromoustakos |
source |
3 |
| 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 |
| SUGI |
1997 |
Using Higher Order Asymptotics to Improve P-values and Confidence Intervals Given by PROC MIXED |
Ben Lyons,
Dawn Peters |
source |
5 |
| SESUG |
1996 |
Macro for Pairwise Reliability Indicators |
Carl M. Russell |
|
3 |
| 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 |
| WUSS |
1996 |
The Intraclass Correlation: What Is It and Why Do We Care? |
David J. Pasta |
source |
6 |
| SEUGI |
1996 |
Mainframe directions |
Werner Bundschuh |
source |
24 |
| SUGI |
1996 |
A Plan to Implement the LlMU Model by a Slight Modification of the Current MIXED Procedure |
Mark X. Norleans |
source |
5 |
| SUGI |
1996 |
Analysis of Unbalanced Mixed Model Data |
Ramon C. Littell |
source |
6 |
| 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 |
Passing Statistical Results from SAS Procedures to Word Documents |
Kem Phillips |
source |
3 |
| 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 |
| SUGI |
1996 |
The Use of the SAS Programming Language and Procedures to Model and Process Data Used in Creating the New U.S. Mortality Atlas |
Gretchen K. Jones,
Linda Williams Pickle,
Michael Mungiole |
source |
6 |
| 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 |
| 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 |
| SESUG |
1995 |
Intraclass Correlation Reliability Estimation Using the GLM and MIXED Procedures |
Maribeth H. Johnson |
|
5 |
| 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 |
Adjusted F-Tests for Repeated Measures with the MIXED Procedure |
S. Paul Wright |
source |
6 |
| SUGI |
1995 |
Calculating Confidence Intervals on Proportions of Variability Using the VARCOMP and IML Procedures |
Annette M. Green,
David Umbach |
source |
6 |
| 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 |
| WUSS |
1994 |
A SAS MACRO for the Ricardian Model of International Trade |
Zaki Eusufzai |
source |
17 |
| WUSS |
1994 |
An Effective Method to Construct Coefficients in CONTRAST and ESTIMATE Statements Used in ANOVA |
George C. J. Fernandez |
source |
17 |
| MWSUG |
1994 |
Alternative Approaches to Mixed Linear Models |
George W. Pasdirtz |
|
6 |
| SESUG |
1994 |
SAS 6.09 on a CONVEX C3840: First Impressions |
Kenneth A. Hardy,
Sally M. Muller |
|
8 |
| 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 |
Application of Random-Effects Model for Categorical Data to Antiemetic Clinical Trials in Cancer Patients |
Regina Louie,
Alex Yaroshinsky |
source |
5 |
| SUGI |
1994 |
Combined Estimates of Carryover Differences in Mixed-Model Procedure |
Louis Munyakazi,
Richard L. Hintz,
B. D. Selby |
source |
4 |
| SUGI |
1994 |
Estimating Components of Variance for a Linear Model Having a Mixed Fixed/Random Factor in a Large Data Structure |
Dawn VanLeeuwen,
N. Scott Urquhart |
source |
5 |
| SUGI |
1994 |
Mixed Model Analysis of Data: Transition from GLM to MIXED |
Ramon C. Littell |
source |
8 |
| SUGI |
1994 |
Recent Issues in Statistical Process Control: SAS Solutions USing Statistical Modeling Procedures |
Robert N. Rodriguez |
source |
18 |
| SUGI |
1994 |
SAS 6.09 on a CONVEX C3840: First Impressions |
Kenneth A. Hardy,
Sally M. Muller |
source |
8 |
| SUGI |
1994 |
SAS Tools for Assessing Gage Repeatability and Reproducibility |
Julie A. LaBarr |
source |
10 |
| 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 |
| SEUGI |
1993 |
EEG Multi-variate Traces Analysed Using PROC MIXED |
Tracy Parker |
source |
10 |
| SEUGI |
1993 |
The Analysis of Repeated Measures Designs Using the SAS System |
Alun Bedding |
source |
9 |
| SESUG |
1993 |
Repeated Measures Using PROC MIXED Instead of PROC GLM |
James H. Roger,
Michael Kenward |
|
10 |
| SEUGI |
1992 |
Output Delivery System |
Thomas J. R. Emmerich |
source |
8 |
| SUGI |
1992 |
A SAS Macro for Performing Analyses of Random Effect Models of Longitudinal Data Using the IML Procedure |
Greg A. Grandits,
Patricia Grambsch,
Thomas Louis |
source |
6 |
| SUGI |
1992 |
Future Directions in Working with Procedure Output |
Christopher R. Olinger,
Robert S. Ray |
source |
8 |
| NESUG |
1991 |
Two Measures of Rating Reliability |
Peter P. Gaccione |
|
7 |
| SEUGI |
1991 |
Future Directions of Statistical Software with the SAS System |
David M. DeLong |
source |
20 |
| SUGI |
1991 |
Confidence Intervals for Contrasts in the Unbalanced Analysis of Variance Using SAS/IML Software |
John Ilgenfritz,
Anand K. Seth |
source |
6 |
| SUGI |
1991 |
Mixed Models: A Future Direction |
Russell D. Wolfinger,
Randall D. Tobias,
John P. Sall |
source |
9 |
| SUGI |
1991 |
The Use of the SAS System in Statistical Training |
William L. Sanders |
source |
4 |
| SUGI |
1990 |
ANALYSIS OF COVARIANCE: REPEATED IfEASURES AND SPLIT-Plur DESIGNS |
George A. Milliken |
source |
10 |
| 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 |
A SAS Matrix Software Macro for Testing the Random Effects in Random Models with Unequal Cell Frequencies in the Last Stage |
Jose Gallo,
Andre I. Khuri,
Richard MacElderry |
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 |
1989 |
Variance Component Analysis |
Ronald R. Hocking |
source |
4 |
| 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 |
1983 |
On the Viability of Some ANOVA-based Mixed Model Estimates |
Kenneth L. Koonce,
W.G. Warren |
source |
8 |
| SUGI |
1982 |
Approaches to Estimation and Testing in the Mixed Model |
R. Kirk Steinhorst |
source |
|
| 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 |
1980 |
Nonorthogonal Analysis of Balanced Data |
Dale O. Everson,
R. Kirk Steinhorst |
source |
5 |
| SUGI |
1980 |
Recent Developments in BMDP of Special Interest to SAS Users |
James W. Frane |
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 |
| SUGI.ONE |
1976 |
Calculating Coefficients in Expected Mean Squares Using SAS. |
Henry K. Hess |
source |
14 |
| SUGI.ONE |
1976 |
Use of the Harvey Procedure |
Walter R. Harvey |
source |
3 |
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