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687 papers and 4 presentations; 602 titles.

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Conference × Year × Title × Authors Extras Pages
WUSS 2026 The (ODS) Output of Your Desires: a Tool-kit for Creating Designer Reports and Data Sets Louise S. Hadden source 12
PharmaSUG CN 2026 Handling Missing Data in Analgesia Clinical Trials and Corresponding SAS Implementation Jingbo Zhu,
Jiehan Zhang		 source 17
PharmaSUG 2026 The (ODS) Output of Your Desires: Creating Designer Reports and Data Sets Louise S. Hadden source 12
PHUSE EU 2025 Multiple Imputations Overview of Missing Data Problem, Solution Methods and SAS Implementation Dmytro Kalinin source
presentation source		 13
MWSUG 2025 The (ODS) Output of Your Desires: Creating Designer Reports and Data Sets Louise S. Hadden source 12
SESUG 2025 Forecasting the U.S. Home Vacancy Rate using ARIMA Joseph Maina,
Abdelmonaem Jornaz		 12
SESUG 2025 The (ODS) Output of Your Desires: Creating Designer Reports and Data Sets Louise S. Hadden 12
SESUG 2025 Writing ESTIMATE statements to compare continuous scores over time overall and by group Alexis Wardell,
Allison M. Deal		 18
WUSS 2025 The (ODS) Output of Your Desires: Creating Designer Reports and Data Sets Louise S. Hadden source 12
PharmaSUG 2025 The (ODS) Output of Your Desires: Creating Designer Reports and Data Sets Louise S. Hadden source 12
SESUG 2024 Using SAS In Analyzing Trends in Corn Yields, Surface Temperature, and Precipitation in U.S. South Atlantic Census Division States Abdullah Khan source 31
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 Integration of an R Language Function Within SAS to Perform Conditional Multivariate Saddlepoint Approximation Christopher Johnson source 8
PharmaSUG CN 2024 Implementation on concentration-QTc modeling Daoqing Li,
Deli Cao		 source 20
PharmaSUG 2024 Bayesian Methods in Survival Analysis: Enhancing Insights in Clinical Research Vadym Kalinichenko source 11
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
PHUSE US 2024 SAS PROC MI: Your Impeccable Tool for Enhanced Data Analysis Through the Lens of Multiple Imputation Anush Kurghinyan,
Shahrzad Talebian		 source
presentation source		 7
PHUSE EU 2023 Detroit, Michigan: A Case Study for DEI Via Decentralised Clinical Trials (DCTs) Mark Rothe source
presentation source		 26
SESUG 2023 Wald Tests in Mixed Models - a Warning David A. Dickey source 20
PharmaSUG 2023 Using the R interface in SAS to Call R Functions and Transfer Data Bruce F. Gilsen source 16
SESUG 2022 Embracing Cross-Loading to Improve Latent Variable Models Fit: A comparison of available options in SAS, Mplus, and R Kevin B. Gittner,
Niloofar Ramezani,
Katherine Mobley		 source 26
PharmaSUG 2022 A SAS macro wrapper for an efficient Deming regression algorithm via PROC IML: The Wicklin method Natasha Oza,
Ben Wang,
Jesse Albert Canchola		 source 13
SESUG 2021 Missing Value Imputation Ross Bettinger source 34
SESUG 2021 Using QUANTREG to Examine time and Drug on Histamine HA level in Mice Abbas S. Tavakoli,
Navid S. Tavakoli		 source 7
PharmaSUG 2021 Mitigating Multicollinearity: Using Regulation Techniques to Minimize the Effect of Collinearity Deanna Naomi Schreiber-Gregory source 23
SGF 2021 A SAS Macro to Perform Bootstrapping for Internal Validation of Time-Dependent Area Under the Curve Jialin Han,
Jiali Ling,
Maria E. Montez-Rath,
Margaret R. Stedman		 source 9
SGF 2021 Bayesian Analysis of GLMMs Using PROC BGLIMM Walter W. Stroup source
pdf		 25
PHUSE EU 2020 Incomplete Data in Longitudinal Studies: Continuous and Dichotomous Outcome [presentation] Ana Grecu source
video		 20
PHUSE EU 2020 MI FOR MI, OR HOW TO HANDLE MISSING INFORMATION WITH MULTIPLE IMPUTATION Daria Shamaida source
video
presentation source		 8
SESUG 2020 Outlier Detection and Treatment Ross Bettinger source 29
SGF 2020 A Warning about Wald Tests David A. Dickey source 20
SGF 2020 Dealing with Missing Data in Epidemiological and Clinical Research Andrew T. Kuligowski,
Lida Gharibvand		 source 6
SGF 2020 Is it possible to reduce smoking by increasing taxes? An analysis on Danish data using SAS software Anders Milhøj source 13
SGF 2020 Mixed-Effects Models and Complex Survey Data with the GLIMMIX Procedure L. Grisell Diaz-Ramirez,
Bocheng Jing		 source 10
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 Using the R interface in SAS to Call R Functions and Transfer Data Bruce F. Gilsen source 17
PHUSE EU 2019 Multiple imputation as a valid way of dealing with missing data Vadym Kalinichenko source
presentation source		 11
SESUG 2019 Glass Box Neural Networks Ross Bettinger source 14
SESUG 2019 Intervention at the Library: Assessing the Effect of an Event David A. Dickey,
John Vickery		 source 19
SESUG 2019 Macros for Neural Network Modeling Ross Bettinger source 23
SESUG 2019 The Best of Both Worlds: Forecasting Using Time Series with Inputs David A. Dickey source 19
SESUG 2019 Using the R interface in SAS to Call R Functions and Transfer Data Bruce F. Gilsen source 17
SCSUG 2019 Do you know when your data is lying to you? The HOW of Regression Analysis with Quantitative and Qualitative Variables Steven C. Myers source 20
SCSUG 2019 Explore your data before you rush to analysis, you will thank me later: explorations in cross section data Steven C. Myers source 28
MWSUG 2019 Do undergraduates need prerequisites for common courses? Lin Qi,
Archana Chinnaswamy,
Miriam McGaugh		 6
MWSUG 2019 Explore your data before you rush to analysis, you will thank me later: explorations in cross section data Steven C. Myers 28
MWSUG 2019 Logistic Regression, Basics and Beyond Bruce S. Lund 35
MWSUG 2019 Surviving Survival Analysis 101: Making the Likelihood Ratio Test Easier Using a Macro Katelyn Ware,
Rachel Baxter		 13
MWSUG 2019 Using ODS Trace (DOM), Procedural Output and ODS Output Objects to Create the Output of Your Dreams Louise S. Hadden 26
WUSS 2019 General, Age-Specific, and Total Fertility Rates in Montana, 2008-2017 Matthew Ringel source 7
PharmaSUG 2019 Regulation Techniques for Multicollinearity: Lasso, Ridge, and Elastic Nets Deanna Naomi Schreiber-Gregory,
Karlen Bader		 source 23
PharmaSUG 2019 Statistical application in Image Processing by Integrating C and SAS Vidhyavathi Venkataraman,
Srinand Ponnathapura Nandakumar,
Anupama Datta		 source 11
PharmaSUG 2019 With a Trace: Making Procedural Output and ODS Output Objects Work For You Louise S. Hadden source 26
SGF 2019 A Selective Overview of Panel Data with Applications in SAS Oral Capps source 26
SGF 2019 Analyzing Structural Causal Models using the CALIS Procedure Banoo Madhanagopal,
John Amrhein		 source 23
SGF 2019 Causal Analyses Using Structural Equation Models Banoo Madhanagopal,
John Amrhein		 source 23
SGF 2019 Conducting Tests in Multivariate Regression Chii-Dean Joey Lin source 13
SGF 2019 Regulation Techniques for Multicollinearity: Lasso, Ridge, and Elastic Nets Deanna Naomi Schreiber-Gregory source 23
SGF 2019 SAS Enterprise Miner and SAS Visual Data Mining and Machine Learning Hand Shake Jagruti Kanjia,
Dominique Latour,
Holly Sweeney		 source 35
SGF 2019 SCORE! Techniques for Scoring Predictive Regression Models Using SAS/STAT Software Phil Gibbs,
Randy Tobias		 source 18
SGF 2019 The Best of Both Worlds: Forecasting Using Time Series with Inputs David A. Dickey source 19
SGF 2019 Using SAS Procedures to Fit Rasch Models Tianshu Pan,
Yumin Chen		 source 10
SGF 2019 Using the R interface in SAS to Call R Functions and Transfer Data Bruce F. Gilsen source 17
SGF 2019 Working with ODS Trace Statement and ODS Output Objects Louise S. Hadden source 26
SGF 2019 Zero-Inflated and Zero-Truncated Count Data Models with the NLMIXED Procedure Robin High source 18
SESUG 2018 Computing Predicted Values and Residuals from Data Sets Containing Classification Variables with Large Numbers of Levels Jamie McClave Baldwin,
Ramon C. Littell,
James McClave		 source 14
SESUG 2018 Forecasting: Something Old, Something New David A. Dickey source 26
SESUG 2018 Regulation Techniques for Multicollinearity: Lasso, Ridge, and Elastic Nets Deanna Naomi Schreiber-Gregory,
Henry M. Jackson		 source 23
SESUG 2018 Using the R interface in SAS to Call R Functions and Transfer Data Bruce F. Gilsen source 17
MWSUG 2018 Assessing Model Adequacy in Proportional Hazards Regression Michael G. Wilson 37
MWSUG 2018 Bootstrap Linear Mixed-Effects Models using SAS Procedures Adams Kusi Appiah 17
MWSUG 2018 How to Score Big with SAS Solutions: Various Ways to Score New Data with Trained Models Scott Koval 6
MWSUG 2018 Regularization Techniques for Multicollinearity: Lasso, Ridge, and Elastic Nets Deanna Naomi Schreiber-Gregory,
Karlen Bader		 23
WUSS 2018 Forecasting: Something Old, Something New David A. Dickey source 26
WUSS 2018 Oops, I D-I-D It Again! Advanced Difference-in-Differences Models in SAS Margaret Warton,
Melissa Parker		 source 17
WUSS 2018 Regulation Techniques for Multicollinearity: Lasso, Ridge, and Elastic Nets Deanna Naomi Schreiber-Gregory source 23
PHUSE US 2018 Methods for Handling Concentration Values Below the Limit of Quantification in PK Studies James R. Johnson source
presentation source		 9
PharmaSUG 2018 Multicollinearity: What Is It and What Can We Do About It? Deanna Naomi Schreiber-Gregory source 13
SGF 2018 Alternative Variance Parameterizations in Count Data Models Robin High source 14
SGF 2018 Fitting Compartment Models Using PROC NLMIXED Raghavendra Rao Kurada,
Fang K. Chen		 source 26
SGF 2018 Forecasting: Something Old, Something New David A. Dickey source 26
SGF 2018 Getting More Insight into Your Forecast Errors with the GLMSELECT and QUANTSELECT Procedures Gerhard Svolba source 26
SGF 2018 Getting Started with Survival Analysis Marc Huber source 76
SGF 2018 Insights into Using the GLIMMIX Procedure to Model Categorical Outcomes with Random Effects Kathleen Kiernan source 23
SGF 2018 Location Matters: Evidence from Spatial Econometric Analysis of Opioid Prescription Rates Jonathan Mccopp source 21
SGF 2018 Measuring Response to the Ultimate Driving Machine: Consumer Sentiments and Brand Advertising Amit K Ghosh,
Goutam Chakraborty,
Praveen Kumar Kotekal		 source 8
SGF 2018 New Ways to Incorporate Continuous Predictors in Generalized Linear Models Anthony Salis,
Angela Wu,
Gordon Johnston		 source 15
SGF 2018 Penalized Variable Selection and Quantile Regression in SAS : An Overview Russell M. Lavery source 28
SGF 2018 Regime-Switching Models: Capturing Structural Changes in Time Series Xilong Chen,
Ji Shen		 source 14
SGF 2018 Scalable Cloud-Based Time Series Analysis and Forecasting Thiago Quirino,
Michael J. Leonard,
Ed Blair		 source 22
SGF 2018 Using SAS for Multiple Imputation and Analysis of Longitudinal Data Patricia A. Berglund source 24
SGF 2018 Using SAS to Estimate Lagged Coefficients with the %partitionedGMM Macro Kyle Irimata,
Jeffrey Wilson		 source 8
SESUG 2017 Missing Data and Complex Sample Surveys Using SAS: The Impact of Listwise Deletion vs. Multiple Imputation Methods on Point and Interval Estimates when Data are MCAR, MAR, and MNAR Listwise Deletion source 26
SESUG 2017 Multicollinearity: What Is It, Why Should We Care, and How Can It Be Controlled? Deanna Naomi Schreiber-Gregory,
Henry M. Jackson		 source 12
PHUSE EU 2017 The Model Statistician Insights into Model Selection Techniques in Clinical Trials Peter Williams source
presentation source		 6
MWSUG 2017 Correcting for Selection Bias in a Clinical Trial Shana Kelly 8
MWSUG 2017 Unconventional Statistical Models with the NLMIXED Procedure Robin High 14
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 Multicollinearity: What Is It and What Can We Do About It? Deanna Naomi Schreiber-Gregory source 12
SGF 2017 %SURVEYGENMOD Macro: An Alternative to Deal with Complex Survey Design for the GENMOD Procedure Alan Ricardo da Silva source 28
SGF 2017 A SAS Macro for Covariate Specification in Linear, Logistic, and Survival Regression Sai Liu source
zip		 19
SGF 2017 Analyzing Residuals in a PROC SURVEYLOGISTIC Model Bogdan Gadidov source 8
SGF 2017 Estimation Strategies Involving Pooled Survey Data Taylor Lewis source 15
SGF 2017 Fitting Complex Statistical Models with NLMIXED and MCMC Procedures Robin High source 14
SGF 2017 GMM Logistic Regression with Time-Dependent Covariates and Feedback Processes in SAS Jeffrey Wilson source 7
SGF 2017 Interrupted Time Series Power Calculation using DO Loop Simulations Nigel Rozario,
Andrew McWilliams,
Charity Moore		 source 15
SGF 2017 More Than Matrices: SAS/IML Software Supports New Data Structures Rick Wicklin source 19
SGF 2017 Multicollinearity: What Is It, Why Should We Care, and How Can It Be Controlled? Deanna Naomi Schreiber-Gregory source 12
SGF 2017 Predictive Models: Storing, Scoring, and Evaluating Matthew Duchnowski source 10
SGF 2017 Price Recommendation Engine for Airbnb Praneth Guggilla,
Singdha Gutha,
Goutam Chakraborty		 source 10
SGF 2017 PROC LOGISTIC: Using New SAS 9.4 Features for Cumulative Logit Models with Partial Proportional Odds Paul Hilliard source
zip
pdf		 16
SGF 2017 Where Does Cleopatra Really Belong? An Analysis of Slot Machine Placement and Performance Using SAS Stephen Tam source 12
SESUG 2016 A Short Introduction to Longitudinal and Repeated Measures Data Analyses Leanne Goldstein source 19
SESUG 2016 Missing Data and Complex Sample Surveys Using SAS: The Impact of Listwise Deletion vs. Multiple Imputation on Point and Interval Estimates when Data are MCAR and MAR Anh P. Kellermann,
DeAnn Trevathan,
Jeffrey D. Kromrey		 source 12
SESUG 2016 Surviving the Interim: Insights Into Interim Survival Analyses Venita DePuy source 31
SESUG 2016 Using JMP to apply Decision Trees and Random Forests as Screening Tools for Limiting Candidate Predictors in Regression Models Jason Brinkley source 10
PHUSE EU 2016 Considerations in the Use of Propensity Scoresin Observational Studies Lawrence Rasouliyan,
Estel Plana		 source
presentation source		 17
MWSUG 2016 An Animated Guide: Penalized variable selection techniques in SAS and Quantile Regression Russell M. Lavery,
Peter Flom		 24
MWSUG 2016 Automating the Process of Generating Publication Quality Regression Tables through SAS Base Programming Ji Qi 16
MWSUG 2016 Fitting Complex Statistical Models with PROCs NLMIXED and MCMC Robin High 16
MWSUG 2016 Fixed Item Parameter Calibration with MMLE-EM Using a Fixed Prior in SAS/IML Sung-Hyuck Lee,
Hongwook Suh		 7
WUSS 2016 Fitting Threshold Models using the SAS Procedures NLIN and NLMIXED Todd Coffey source 11
WUSS 2016 MIghty PROC MI to the rescue! Cynthia Alvarez source 10
SGF 2016 A SAS Macro for Geographically Weighted Negative Binomial Regression Alan Ricardo da Silva,
Thais Rodrigues		 source
zip		 20
SGF 2016 A Short Introduction to Longitudinal and Repeated Measures Data Analyses Leanne Goldstein source 19
SGF 2016 Analysis of Grades for University Students Using Administrative Data and the IRT Procedure Sara Armandi source 13
SGF 2016 Analyzing Non-Normal Binomial and Categorical Response Variables under Varying Data Conditions Niloofar Ramezani source 16
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 Comparative Regional Analysis of Bacterial Pneumonia Readmission Patients in the Medicare Category Heramb Joshi,
Goutam Chakraborty,
William Paiva,
Aditya Sharma		 source 12
SGF 2016 Fitting Multilevel Hierarchical Mixed Models Using PROC NLMIXED Raghavendra Kurada source 15
SGF 2016 Generalized Linear Models for Non-Normal Data Theresa H. Ngo source 5
SGF 2016 Latent Class Analysis Using the LCA Procedure Patricia A. Berglund source 18
SGF 2016 Linear State Space Models in Retail and Hospitality Beth Cubbage source 10
SGF 2016 Outlier Detection Using the Forward Search in SAS/IML Studio Jos Polfliet source
zip		 12
SGF 2016 Quantitle Regression versus Ordinary Least Squares Regression Ruth Croxford source 10
SGF 2016 Real-Time Predictive Modeling of Key Quality Characteristics Using Regularized Regression: SAS Procedures GLMSELECT and LASSO Jon M. Lindenauer source 10
SGF 2016 SAS Macro for Generalized Method of Moments Estimation for Longitudinal Data with Time-Dependent Covariates Katherine Cai,
Jeffrey Wilson		 source 9
SGF 2016 Spatial Dependence, Nonlinear Panel Models, and More New Features in SAS/ETS 14.1 Jan Chvosta source 11
SGF 2016 Tips and Strategies for Mixed Modeling with SAS/STAT Procedures Phil Gibbs source 21
SGF 2016 What's the Difference? David A. Dickey source 17
SCSUG 2015 Using SAS Software to Determine the Mixed Rotterdam Demand Model Parameters and Test Statistical References Maryam Tabarestani,
Hector Zapata		 23
MWSUG 2015 Can You Stop the Guesswork in Your Marketing Budget Allocation? Marketing Mixed Modeling Using SAS Can Help! Delali Agbenyegah 7
MWSUG 2015 SAS Software as an Essential Tool in Statistical Consulting and Research Erika Larsen,
Timothy E. O'Brien		 13
MWSUG 2015 Transitions in Depressive Symptoms After 10 Years of Follow-up Using PROC LTA in SAS and Mplus Seungyoung Hwang 11
PHUSE EU 2015 Facing Your Fear of the Unknown - Handling Missing Data Amanda Reilly source
presentation source		 7
SESUG 2015 Adaptive Fractional Polynomial Modeling in SAS George J. Knafl source 10
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 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 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 Data Analyses in Multivariate Regression Chii-Dean Joey Lin source 9
WUSS 2015 Generalized Estimating Equations for Depression Dose Regimes Karen Walker source 8
WUSS 2015 Introduction to SAS Quantile Regression (PROC QuantSelect and PROC QuantReg ) Peter L. Flom source 25
WUSS 2015 Sample Size Convergence of Denominator Degrees of Freedom Method Options in SAS PROC MIXED Timothy Banh source 13
PharmaSUG CN 2015 Hands-on Tutorial for Piecewise Linear Mixed-effects Models Using SAS PROC MIXED Qinlei Huang 15
PharmaSUG 2015 Analysis Methods for a Sequential Parallel Comparison Design (SPCD) Harry Haber,
James Zuazo,
Linda LaMoreaux		 source 11
SGF 2015 A Model Family for Hierarchical Data with Combined Normal and Conjugate Random Effects [presentation] Geert Molenberghs source 54
SGF 2015 Data Summarization for a Dissertation: A Grad Student How-To Paper Elisa L. Priest,
Ashley Collinsworth		 source 8
SGF 2015 Double Generalized Linear Models Using SAS: The %DOUBLEGLM Macro Paulo Silva,
Alan Ricardo da Silva		 source
zip		 16
SGF 2015 Getting Your Hands on Reproducible Graphs Rebecca Ottesen,
Leanne Goldstein		 source 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 Imputing Missing Data using SAS Christopher Yim source 9
SGF 2015 Lasso Regularization for Generalized Linear Models in Base SAS Using Cyclical Coordinate Descent Robert Feyerharm source 10
SGF 2015 Modelling Operational Risk Using Extreme Value Theory and Skew t-Copulas via Bayesian Inference Using SAS Betty Johanna Garzon Rozo source 20
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 Imputation Using the Fully Conditional Specification Method: A Comparison of SAS, Stata, IVEware, and R Patricia A. Berglund source 17
SGF 2015 Predicting Readmission of Diabetic Patients Using the High-Performance Support Vector Machine Algorithm of SAS Enterprise Miner 13.1 Hephzibah Munnangi,
Goutam Chakraborty		 source 10
SGF 2015 Preparing Output from Statistical Procedures for Publication, Part 1: PROC REG to APA Format Vincent DelGobbo,
Peter L. Flom		 source 27
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 Survival Analysis with Survey Data Joseph C. Gardiner source 17
SGF 2015 Using and Understanding the LSMEANS and LSMESTIMATE Statements David J. Pasta source 20
SESUG 2014 Analyzing Multilevel Models with the GLIMMIX Procedure Min Zhu source 19
SESUG 2014 Don't be binary! Tales of Non-binary Categorical Regression Charlotte Baker source 6
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 Small Sample Bayesian Factor Analysis Dirk Heerweghm source
presentation source		 18
MWSUG 2014 Comparing regression, propensity matching and coarsened exact matching in healthcare observational studies using SAS: An example from the Medical Expenditure Panel Survey (MEPS) Douglas Thompson 16
WUSS 2014 Options in Estimating Nonlinear Mixed Models: Quadrature points and Approximation Methods Nate Smith,
Shelley A. Blozis		 source 7
WUSS 2014 Using and Understanding LSMEANS and LSMESTIMATE David J. Pasta source 20
PharmaSUG 2014 Factor Analysis of Scale for Assessment of Negative Symptoms using SAS Software Ben Adeyi,
David Shen		 source 8
PharmaSUG 2014 Using SAS to Calculate and Compare Adjusted Relative Risks, Odds Ratios, and Hazard Ratios Besa Smith,
Tyler C. Smith		 source 23
SGF 2014 A SAS Macro for Complex Sample Data Analysis Using Generalized Linear Models Paulo Henrique Dourado da Silva,
Alan Ricardo da Silva		 source 19
SGF 2014 Accelerated Tests as an Effective Means of Quality Improvement Bobby Gutierrez source 9
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 Multilevel Models with the GLIMMIX Procedure Min Zhu source 18
SGF 2014 Case-Level Residual Analysis in the CALIS Procedure Catherine Truxillo source 17
SGF 2014 Confirmatory Factor Analysis and Structural Equation Modeling of Non-cognitive Assessments Using PROC CALIS Steven L. Holtzman source 11
SGF 2014 Examples of Logistic Modeling with the SURVEYLOGISTIC Procedure Rob Agnelli source 17
SGF 2014 Getting Started with the SAS/IML Language Rick Wicklin source 21
SGF 2014 Got Randomness? SAS for Mixed and Generalized Linear Mixed Models David A. Dickey source 12
SGF 2014 Is Nonlinear Regression Throwing You a Curve? New Diagnostic and Inference Tools in the NLIN Procedure Biruk Gebremariam source 16
SGF 2014 Item Response Theory: What It Is and How You Can Use the IRT Procedure to Apply It Xinming An,
Yiu-Fai Yung		 source 14
SGF 2014 Modeling Fractional Outcomes with SAS Wensui Liu,
Jason Xin		 source 17
SGF 2014 Nonnegative Least Squares Regression in SAS Matthew Duchnowski source 5
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 SAS/STAT 13.1 Round-Up Bob Rodriguez,
Maura E. Stokes		 source 25
SGF 2014 Scenarios Where Utilizing a Spline Model in Developing a Regression Model Is Appropriate Ning Huang source 9
SGF 2014 Sensitivity Analysis in Multiple Imputation for Missing Data Yang Yuan source 12
SGF 2014 Simulating Portfolio Losses from Adverse Events: Applications to the Insurance and Finance Industries Mahesh V. Joshi,
Jan Chvosta		 source
zip		 20
WUSS 2013 A Tutorial on PROC LOGISTIC Arthur X. Li source 19
WUSS 2013 Competing risks regression: Big Data issues from modest sample sizes Katharine Kirby,
Deborah Barnes,
W. John Boscardin		 source 4
WUSS 2013 How to Compute Custom Hazard Ratio in SAS (V8.2&V9.2) PHREG Procedure Liguo Cheng,
Yu Li		 source 8
WUSS 2013 Simulation in SAS with Comparisons to R Chelsea Lofland,
Rebecca Ottesen		 source 25
WUSS 2013 User-Specified Likelihood Expressions Using NLMIXED and the GENERAL Statement Melissa McTernan,
Shelley A. Blozis		 source 4
WUSS 2013 Using PROC ARIMA to Model Trends in US Home Prices Ross Bettinger source 13
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 Dealing with Missing Data for Credit Scoring Steve Fleming source 7
SESUG 2013 Fit Discrete Distributions via SAS Macro Fit Discrete Distributions source 5
SESUG 2013 GLIMMIX_Rasch: A SAS Macro for Fitting the Dichotomous Rasch Model Yi-Hsin Chen source 10
PHUSE EU 2013 Around the World in Three Statistical Models: Determing the Level of Measurement Invariance Across Countries of a PRO Instrument Dirk Heerwegh source
presentation source		 29
PHUSE EU 2013 Extensions of Cox Model for Non-Proportional Hazards Purpose Jadwiga Borucka source
presentation source		 10
MWSUG 2013 A Tutorial on PROC LOGISTIC Arthur X. Li 19
MWSUG 2013 Adventures in Path Analysis and Preparatory Analysis Brandy R. Sinco,
Phillip L. Chapman		 19
MWSUG 2013 Dealing with Data below the Detection Limit: Limit Estimation and Data Modeling Mark Bailey,
Diane K. Michelson		 21
MWSUG 2013 Ideas and Examples in Generalized Linear Mixed Models David A. Dickey 12
MWSUG 2013 Statistical Models for Proportional Outcomes Wensui Liu,
Kelly Zhao		 17
NESUG 2013 With a Trace: Making Procedural Output and ODS Output Objects Work For You Louise S. Hadden 23
PharmaSUG 2013 Combining Analysis Results from Multiply Imputed Categorical Data Bohdana Ratitch,
Ilya Lipkovich,
Michael O'Kelly		 source 19
SGF 2013 A Flexible Method to Apply Multiple Imputation Using SAS/IML Studio Lisa M. Lix,
Xue Yao		 source
pdf		 9
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 Are You Discrete? Patients' Treatment Preferences and the Discrete Choice Experiment Beeya Na,
Eric P. Elkin		 source 6
SGF 2013 Assessing Model Adequacy in Proportional Hazards Regression Michael G. Wilson source 36
SGF 2013 Being Continuously Discrete (or Discretely Continuous): Understanding Models with Continuous and Discrete Predictors and Testing Associated Hypotheses David J. Pasta source 19
SGF 2013 Calculating Subset-Weighted Analysis in PROC SURVEYFREQ and PROC GENMOD David M. Thompson,
Jessica Hale,
Paul Darden		 source
pdf		 7
SGF 2013 Considerations and Techniques for Analyzing Domains of Complex Survey Data Taylor Lewis source 12
SGF 2013 Cox Proportional Hazard Model Evaluation in One Shot Polina Kukhareva source 11
SGF 2013 Getting Started with the SAS/IML Language Rick Wicklin source 21
SGF 2013 Having an EFFECT: More General Linear Modeling and Analysis with the New EFFECT Statement in SAS/STAT Software Jill Tao,
Kathleen Kiernan,
Phil Gibbs,
Randy Tobias		 source 14
SGF 2013 Models for Ordinal Response Data Robin High source 16
SGF 2013 Predicting Health Care Expenditures with the MCMC Procedure Gregory Watson source 12
SGF 2013 Price and Cross-Price Elasticity Estimation Using SAS Dawit Mulugeta,
Jason Greenfield,
Lisa Conley,
Tison Bolen		 source 17
SGF 2013 Quantile Regression in Pharmaceutical Marketing Research George Mu source 4
SGF 2013 The Box-Jenkins Methodology for Time Series Models Theresa H. Ngo source 11
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
SGF 2013 With a Trace: Making Procedural Output and ODS Output Objects Work For You Louise S. Hadden source
pdf		 21
NESUG 2012 A Macro-Driven Approach for Systematically Testing Variables Against a Base Regression Model Jennifer Alessandro,
Bryan Harmon		 7
NESUG 2012 A Model for Extreme Stacking of Data at Endpoints of a Distribution Robert J. Gallop 8
NESUG 2012 Introducing the FMM Procedure for Finite Mixture Models Maura E. Stokes 22
NESUG 2012 With a Trace: Making Procedural Output and ODS Output Objects Work For You Louise S. Hadden 11
PHUSE EU 2012 Multicollinearity Diagnostics in Statistical Modeling and Remedies to Deal with it Using SAS Harshada Joshi,
Swapna Deshpande		 source
presentation source		 12
SESUG 2012 Multiple Imputation for Ordinal Variables: A Comparison of SUDAAN's PROC IMPUTE vs. PROC MI Multiple Imputation source 12
SESUG 2012 Tips and Strategies for Mixed Modeling with SAS/STAT Procedures Kathleen Kiernan,
Jill Tao,
Phil Gibbs		 source 18
MWSUG 2012 Combined Forecasts: What to Do When One Model Isn't Good Enough Ed Blair,
Michael J. Leonard,
Bruce Elsheimer		 14
MWSUG 2012 Methods for Interaction Detection in Predictive Modeling Using SAS Douglas Thompson 13
MWSUG 2012 Modeling Complex Survey Data Taylor Lewis 16
MWSUG 2012 Models for Ordinal Response Data Robin High 11
MWSUG 2012 Tips and Strategies for Mixed Modeling with SAS/STAT Procedures Kathleen Kiernan,
Jill Tao,
Phil Gibbs		 18
WUSS 2012 Being Continuously Discrete (or Discretely Continuous): Understanding Models with Continuous and Discrete Predictors and Testing Associated Hypotheses David J. Pasta source 19
WUSS 2012 Exploratory Factor Analysis with the World Values Survey Diana D. Suhr source 19
WUSS 2012 Sensitivity analysis of nonlinear mixed-effects models for longitudinal data that areincomplete Shelley A. Blozis source 6
WUSS 2012 Survival Analysis with PHREG: Using MI and MIANALYZE to Accommodate Missing Data Arthur L. Carpenter,
Christopher F. Ake		 source 7
WUSS 2012 The Steps to Follow in a Multiple Regression Analysis Theresa H. Ngo source 12
WUSS 2012 Up To Speed With Categorical Data Analysis Maura E. Stokes source 25
PharmaSUG 2012 Are You Discrete? Patients' Treatment Preferences and the Discrete Choice Experiment Beeya Na,
Eric P. Elkin		 source 5
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 The Greatest Hits: ODS Essentials Every User Should Know Cynthia L. Zender source 34
SGF 2012 Analyzing the Time Series of U.S. E-Commerce Using PROC UCM Anders Milhøj source 11
SGF 2012 Combined Forecasts: What to Do When One Model Isn't Good Enough Ed Blair,
Michael J. Leonard,
Bruce Elsheimer		 source 14
SGF 2012 Exploratory Factor Analysis with the World Values Survey Diana D. Suhr source 19
SGF 2012 Finding the Winning Combination: An Application of Multivariate Testing from Digital Marketing Robert Krutsick source 8
SGF 2012 Handling Missing Data by Maximum Likelihood Paul D. Allison source 21
SGF 2012 How Test Length and Sample Size Have an Impact on the Standard Errors for IRT True Score Equating: Integrating SAS and Other Software Yi-Fang Wu source 12
SGF 2012 Including the Salesperson Effect in Purchasing Behavior Models Using PROC GLIMMIX Philippe Baecke,
Dirk Van den Poel		 source 11
SGF 2012 Inflated Beta Regression: Zero, One, and Everything in Between Christopher J. Swearingen,
Maria S. Melguizo,
Zoran Bursac		 source 11
SGF 2012 Introducing the FMM Procedure for Finite Mixture Models David Kessler,
Allen McDowell		 source 22
SGF 2012 Introduction to Predictive Modeling with Examples David A. Dickey source 14
SGF 2012 Tips and Strategies for Mixed Modeling with SAS/STAT Procedures Kathleen Kiernan,
Jill Tao,
Phil Gibbs		 source 18
SGF 2012 Using PROC GAM to Forecast Claims Reserves in the Runoff Triangles Ling Huang source 7
SCSUG 2011 The Greatest Hits: ODS Essentials Every User Should Know Cynthia L. Zender source 34
SCSUG 2011 Using Proc Logistic, SAS Macros and ODS Output to evaluate the consistency of independent variables during the development of logistic regression models. An example from the retail banking industry Alexandros Vidras source 9
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 Eyes on the Road: A Methodology for Analyzing Complex Eye-Tracking Data Eye Tracking source 11
SESUG 2011 Linear Logistic Test Model: Using SAS to Simulate the Decomposition of Item Difficulty by Algorithm, Sample Size, Cognitive Component and Time to Convergence George MacDonald,
Jeffrey D. Kromrey		 source 11
SESUG 2011 On Deck: SAS/STAT 9.3 Maura E. Stokes,
Fang K. Chen		 source 20
WUSS 2011 Assessing resource adequacy uncertainty in California electricity summer demand using the MCMC procedure in SAS Enterprise MinerTM Miguel Garcia-Cerrutti source 12
WUSS 2011 Fitting latency models in epidemiological studies Bryan Langholz source 7
WUSS 2011 On Deck: SAS/STAT 9.3 Maura E. Stokes source 20
WUSS 2011 SAS Essentials III: Statistics for Hamsters AnnMaria De Mars source 18
WUSS 2011 Up To Speed With Categorical Data Analysis Maura E. Stokes source 25
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 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 Using SAS to Create Sales Expectations for Everyday and Seasonal Products Lory Ellebracht,
Jamie Netherton,
Casey Gentry		 10
NESUG 2011 A Comparison of PDLREG and GAM Procedures in Measuring Dynamic Effects Patralekha Bhattacharya 11
NESUG 2011 Confirmatory Factor Analysis and Structural Ehuation Modeling of Non-cognitive Assessments Using PROC CALIS Steven L. Holtzman,
Sailesh Vezzu		 9
NESUG 2011 On Deck: SAS/STAT 9.3 Maura E. Stokes 20
NESUG 2011 SAS Macro for Nonparametric Residual Bootstrap Multilevel Modeling Jichuan Wang,
Peichang Shi,
Avital Cnaan		 6
NESUG 2011 The Greatest Hits: ODS Essentials Every User Should Know Cynthia L. Zender 34
NESUG 2011 Using SAS to Navigate the USDA Forest Servicees Forest Inventory and Analysis Database Matthew Russell,
Philip Radtke,
Aaron Weiskittel		 4
PharmaSUG 2011 Implementation of Pattern-Mixture Models Using Standard SAS/STAT Procedures Bohdana Ratitch,
Michael O'Kelly		 source 10
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 Bivariate Count Data Regression Models: A SAS Macro Program Nan-Ting Chou,
David Steenhard		 source 10
SGF 2011 JMP 9 Add-Ins: Taking Visualization of SAS Data to New Heights Eric Hill source 16
SGF 2011 Making Use of Incomplete Observations in the Analysis of Structural Equation Models: The CALIS Procedures Full Information Maximum Likelihood Method in SAS/STAT 9.3 Yiu-Fai Yung,
Wei Zhang		 source 20
SGF 2011 Modeling Percentage Outcomes: The %Beta_Regression Macro Christopher J. Swearingen,
Maria S. Melguizo,
Zoran Bursac		 source 12
SGF 2011 On Deck: SAS/STAT 9.3 Maura E. Stokes,
Robert N. Rodriguez,
Funda Güneş		 source 20
SGF 2011 PATH and LISMOD Languages in SAS PROC TCALIS for Multigroup Comparisons Fei Gu,
Wei Wu		 source 10
SGF 2011 Repeated Measures Analysis of Correlated Data with Multiple Responses Using SAS Anbuchelvi Jeyabslasingham,
Anpalaki J. Ragavan		 source 10
SGF 2011 The Greatest Hits: ODS Essentials Every User Should Know Cynthia L. Zender source
zip		 34
SGF 2011 Those Confounded Interactions: Building and Interpreting a Model with Many Potential Confounders and Interactions David J. Pasta source 13
SGF 2011 Up To Speed With Categorical Data Analysis Gary G. Koch,
Maura E. Stokes		 source 25
SGF 2011 Using PROC LOGISTIC to Estimate the Rasch Model Tianshu Pan,
Yumin Chen		 source 7
SGF 2011 Using SAS PROC TCALIS for Multigroup Structural Equation Modeling with Mean Structures Fei Gu,
Wei Wu		 source 16
NESUG 2010 Modeling healthcare expenditures using PROC QUANTREG Klaus Lemke 7
NESUG 2010 Multinomial and ordinal logistic regression using SAS Peter L. Flom 12
NESUG 2010 The Next Generation: SAS/STAT 9.22 Maura E. Stokes,
Robert N. Rodriguez,
Robert Cohen		 20
NESUG 2010 The Quest for Causation: An Introduction to Correlation and Regression Analysis Ian Stockwell 9
WUSS 2010 An Introduction to Statistical Tests for the SAS Programmer Sara Beck source 10
WUSS 2010 Dummy Coding for Dummies Kathryn Martin source 10
WUSS 2010 Logit-based Neutral Zone Classification Algorithm with Application to Microbial Community Profiling Rebecca Le source 9
WUSS 2010 Survival Analysis with PHREG: Using MI and MIANALYZE to Accommodate Missing Data Christopher F. Ake source 7
WUSS 2010 The Next Generation: SAS/STAT 9.22 Robert N. Rodriguez source 20
WUSS 2010 Those Confounded Interactions: Building and Interpreting a Model with Many Potential Confounders and Interactions David J. Pasta source 9
PHUSE EU 2010 Assesment of Cox Proportional Hazard Model Adequacy Using PROC PHREG and PROC GPLOT Jadwiga Borucka source
presentation source		 13
MWSUG 2010 An Introduction to Multiple Imputation of Complex Sample Data Using SAS 9.2 Patricia A. Berglund 12
MWSUG 2010 Ideas and Examples in Generalized Linear Mixed Models David A. Dickey 12
MWSUG 2010 Novel Use of SAS Software in Industrial and Biomedical Consulting, Research, and Teaching Timothy E. O'Brien 13
MWSUG 2010 Survival Analysis with PHREG: Using MI and MIANALYZE to Accommodate Missing Data Christopher F. Ake,
Arthur L. Carpenter		 6
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 SAS Macros for Estimating the Attributable Benefit of an Optimal Treatment Regime Jason Brinkley source 12
SESUG 2010 The Next Generation: SAS/STAT 9.22 Maura E. Stokes,
Bob Rodriguez,
Robert A. Cohen		 source 20
PharmaSUG 2010 An Overview of the CLASS, CONTRAST, and HAZARDRATIO Statements in the SAS 9.2 PHREG Procedure Paul T. Savarese,
Michael J. Patetta		 23
PharmaSUG 2010 Linear Mixed Models in Clinical Trials using PROC MIXED Danyang Bing,
Xiaomin He		 12
SGF 2010 An Introduction to Multiple Imputation of Complex Sample Data Using SAS 9.2 Patricia A. Berglund source 12
SGF 2010 An Overview of the CLASS, CONTRAST, and HAZARDRATIO Statements in the SAS 9.2 PHREG Procedure Paul T. Savarese,
Michael J. Patetta		 source 23
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 Getting Correct Results from PROC REG Nathaniel Derby source 14
SGF 2010 Ideas and Examples in Generalized Linear Mixed Models David A. Dickey source 12
SGF 2010 Modeling the Severity of Random Events with the SAS/ETS SEVERITY Procedure Mahesh V. Joshi source 20
SGF 2010 Practicalities of Using ESTIMATE and CONTRAST Statements David J. Pasta source 20
SGF 2010 SAS for Green Energy Solutions in Smart Electric Grid Systems Farhad Islam source 10
SGF 2010 The Next Generation: SAS/STAT 9.22 Maura E. Stokes,
Robert N. Rodriguez		 source 20
SGF 2010 Using Recycled Predictions for Computing Marginal Effects Zhongmin Li,
Geeta Mahendra		 source 10
SGF 2010 Using the NLMIXED Procedure to Fit Linear and Nonlinear Growth Curve Models Mo Zheng source 6
SESUG 2009 A Logistic Regression Model to Predict Freshmen Enrollments Vijayalakshmi Sampath,
Andrew Flagel		 source 12
SESUG 2009 Getting Correct Results from PROC REG Nathaniel Derby 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 Multiple Imputation for Survey Data Analysis Yeats Ye source 7
MWSUG 2009 Getting Correct Results from PROC REG Nathaniel Derby 14
PNWSUG 2009 Getting Correct Results from PROC REG Nathaniel Derby 14
PNWSUG 2009 Wait Wait, Don't Tell Me… You're Using the Wrong Proc! David L. Cassell 11
NESUG 2009 Using the New SURVEY Procedures From a Modeling Perspective Jonas V. Bilenas 13
WUSS 2009 Automating the Process of Scoring a Generalized Linear Model Fitted using PROC GENMOD Prakash Gurumurthy source 9
WUSS 2009 Computing Hazard Ratios and Confidence Intervals for a Two-Factor Cox Model with Interaction Terms Marla J. Husnik,
Jing Wang		 source 10
WUSS 2009 Efficient Statistical Programming? - These Small Steps Make the Difference Keiko I. Powers source 16
WUSS 2009 Getting Correct Results from PROC REG Nathaniel Derby source 14
WUSS 2009 Validating the Bland-Altman Method of Agreement Ryan Fernandez,
George C. J. Fernandez		 source 17
PharmaSUG 2009 Computing Hazard Ratios and Confidence Intervals for a Two-Factor Cox Model with Interaction Terms Jing Wang,
Fred Hutchinson Cancer		 10
PharmaSUG 2009 Image is Almost Everything: Displaying Statistics Via ODS R. Scott Leslie 8
PharmaSUG 2009 The Existence of Maximum Likelihood Estimates for the Logistic Regression Model William F. McCarthy,
Nan Guo		 12
SGF 2009 %QLS SAS Macro: A SAS Macro for Analysis of Longitudinal Data Using Quasi-Least Squares Hanjoo Kim,
Justine Shults		 source 12
SGF 2009 A Flexible Count Data Regression Model Using SAS PROC NLMIXED Nan-Ting Chou,
David Steenhard		 source 14
SGF 2009 Image is Almost Everything: Displaying Statistics Via ODS R. Scott Leslie source 8
SGF 2009 Learning When To Be Discrete: Continuous vs. Categorical Predictors David J. Pasta source 10
WUSS 2008 Comparing efficiency of cross validated partial least squares regression and ridge regression models in predicting spatial variability of total nitrogen concentration in Truckee River, Nevada. Anpalaki J. Ragavan source 13
WUSS 2008 Image is Almost Everything: Displaying Statistics Via ODS R. Scott Leslie source 5
WUSS 2008 Step your way through Path Analysis Diana D. Suhr source 10
SESUG 2008 Count Regression Models in SAS David Steenhard,
Nan-Ting Chou		 source 12
SESUG 2008 Interpreting Three-way Interactions Using SAS Anh Le,
Maribeth H. Johnson		 source 12
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
SESUG 2008 Surviving Survival Analysis - An Applied Introduction Christianna S. Williams source 17
SESUG 2008 Techniques for Evidence-Based Decision Making Using SAS Ian Stockwell source 8
MWSUG 2008 Imputation of Categorical Missing Data: A comparison of Multivariate Normal and Multinomial Methods Holmes Finch,
Matt Margraf		 12
MWSUG 2008 So, Who's Afraid of Nonlinear Regression? Heinz Plaumann 14
PNWSUG 2008 Wait Wait, Don't Tell Me… You're Using the Wrong Proc! David L. Cassell 11
NESUG 2008 Fitting Generalized Additive Models with the GAM Procedure in SAS 9.2 Weijie Cai 14
NESUG 2008 Try, Try Again: Replication-Based Variance Estimation Methods for Survey Data Analysis in SAS 9.2 Pushpal K. Mukhopadhyay 16
PharmaSUG 2008 Sample Size Estimation for Trials of Recurrent Events Kuolung Hu 8
PharmaSUG 2008 The Use of Propensity Scores and Instrumental Variable Methods to Adjust For Treatment Selection Bias R. Scott Leslie 8
PharmaSUG 2008 Using ESTIMATE and CONTRAST Statements for Customized Hypothesis Tests Hanyu Chen 8
SGF 2008 Adventures in ODS: Producing Customized Reports Using Output from Multiple SAS Procedures Stuart D. Long,
Jeffrey M. Abolafia,
Lawrence Park		 source 23
SGF 2008 Convergence Failures in Logistic Regression Paul D. Allison source 11
SGF 2008 Count Data Models in SAS Wensui Liu,
Jimmy Cela		 source 12
SGF 2008 Data Mining Application of Non-Linear Mixed Modeling in Water Quality Analysis Anpalaki J. Ragavan source 14
SGF 2008 Fitting Generalized Additive Models with the GAM Procedure in SAS 9.2 Weijie Cai source 14
SGF 2008 How to Use SAS to Fit Multiple Logistic Regression Models Anpalaki J. Ragavan source 13
SGF 2008 Introduction to Correlation and Regression Analysis Ian Stockwell source 8
SGF 2008 Modeling Zero-Inflated Count Data with Underdispersion and Overdispersion Adrienne Tin source 11
SGF 2008 ODS and Output Data Sets: What You Need to Know Myra A. Oltsik source 13
SGF 2008 Operational Risk: Economic Capital (EC) Modeling with a Loss Distribution Approach Sabri G. Uner source 14
SGF 2008 Structural Equation Modeling and Path Analysis Using PROC TCALIS in SAS 9.2 Yiu-Fai Yung source 20
SGF 2008 The Use of Propensity Scores and Instrumental Variable Methods to Adjust For Treatment Selection Bias R. Scott Leslie,
Hassan Ghomrawi		 source 8
SGF 2008 Try, Try Again: Replication-Based Variance Estimation Methods for Survey Data Analysis in SAS 9.2 Anthony B. An,
Pushpal K. Mukhopadhyay,
Randall D. Tobias,
Donna L. Watts		 source 16
NESUG 2007 Butting Heads on Matched Cohort Analysis Using SAS Software Melvin T. Alexander 12
NESUG 2007 ODS, An Introduction to Creating Output Data Sets Elisabeth Pyle 7
NESUG 2007 PROC LOGISTIC: The Logistics Behind Interpreting Categorical Variable Effects Taylor Lewis 7
NESUG 2007 Using the New SURVEY Procedures From a Modeling Perspective Jonas V. Bilenas 13
SESUG 2007 Data Mining and Investigating Treatment Options of Osteomyelitis with MRSA Hamed Zahedi source 9
SESUG 2007 Integrating SAS and Microsoft .NET for Data Analysis Mai Nguyen,
Shane Trahan,
Patricia Nguyen,
Jonathan Cirella		 source 10
SESUG 2007 Selection Bias Adjustment: Root Canal Therapy and Self-reported Oral Health Mark S. Litaker,
Sandre F. McNeal,
Gregg H. Gilbert		 source 9
WUSS 2007 Data Mining Using SAS Enterprise Miner Randall Matignon source 10
WUSS 2007 Health Outcomes Research Using Time-to-Event Analytic Approaches Tyler C. Smith,
Besa Smith		 source 22
WUSS 2007 The Use of Propensity Scores and Instrumental Variable Methods to Adjust For Treatment Selection Bias R. Scott Leslie source 8
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
SCSUG 2007 A SAS Macro for Hosmer and Lemeshow's Purposeful Selection Model Building Algorithm: Description and Performance David Williams,
Zoran Bursac,
David K. Hosmer		 6
SCSUG 2007 Individual Growth Analysis Using PROC MIXED Maribeth H. Johnson 10
PharmaSUG 2007 Graphing Estimates of Regression Models for Discrete and Limited Dependent Variables Jianming He,
David Budd		 10
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 A Purposeful Selection of Variables Macro for Logistic Regression Zoran Gauss,
C. Heath Williams,
David K. Hosmer,
David W. Bursac		 source 5
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 Latent Class Analysis in SAS-Promise, Problems, and Programming David M. Thompson source 12
SGF 2007 OLS Regression? Auto-Regression? Dynamic Regression? Rodger Zhang source 12
SGF 2007 Repeated Measures Analysis with Clustered Subjects Ramon C. Littell source 11
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
SCSUG 2006 What's New in SAS Enterprise Miner 5.2 Wayne Thompson,
David R. Duling		 10
PHUSE EU 2006 The Hazards of Modelling Proportional Hazards in SAS Erika Daly,
Farzana Sufi		 source 4
SESUG 2006 Combining PROC GENMOD Models with Multinomial Outcomes Using PROC MIANALYZE Marie Gantz source 7
SESUG 2006 Designing Information-Service Products: A Hierarchical Bayesian Approach Nan-Ting Chou source 9
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 Font Color or Highlight? You Name It! Guanjun Feng source 4
WUSS 2006 PROC GENMOD with GEE to Analyze Correlated Outcomes Data Using SAS Tyler C. Smith,
Besa Smith		 source 14
WUSS 2006 Sample Survey Data and the Procs you OUGHT To Be Using David L. Cassell source 13
WUSS 2006 The Basics of Structural Equation Modeling Diana D. Suhr source 19
WUSS 2006 Wait Wait, Don't Tell Me… You're Using the Wrong Proc! David L. Cassell source 11
NESUG 2006 Data Analysis: Beyond the Basics Ian Stockwell 9
NESUG 2006 Logistic Regression Basics Joseph J. Guido,
Paul Winters,
Adam Rains		 7
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 You Can't Stop Statistics Maura E. Stokes,
Robert N. Rodriguez		 32
PharmaSUG 2006 Analyzing Ordinal Repeated Measures Data Using SAS Bin Yang 8
PharmaSUG 2006 Generating Half-normal Plot for Zero-inflated Binomial Regression Zhao Yang,
Xuezheng Sun		 12
SUGI 2006 A Comparison of the MIXED Procedure and the GLIMMIX Procedure Jennifer L. Ferrell source 8
SUGI 2006 Combining the Power of ODS, Data Set Concatenation, and DDE to Output Customized Statistical Results from SAS to Microsoft Excel Navneet K. Dhand,
Jenny-Ann Toribio		 source 10
SUGI 2006 Exploratory or Confirmatory Factor Analysis? Diana D. Suhr source 17
SUGI 2006 Modeling Water Quality Trend in Long Term Time Series Anpalaki J. Ragavan,
George C. J. Fernandez		 source 10
SUGI 2006 Performing Latent Class Analysis Using the CATMOD Procedure David M. Thompson source 8
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 What's New in SAS Enterprise Miner 5.2 Wayne Thompson,
David R. Duling		 source 10
SUGI 2006 You Can't Stop Statistics Maura E. Stokes,
Robert N. Rodriguez		 source 32
SESUG 2005 The Missing Link: Data Analysis with Missing Information Venita DePuy source 9
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 Mining Transactional And Time Series Data Michael J. Leonard 26
MWSUG 2005 What's New And Upcoming In SAS 9 ODS Tim Hunter 38
WUSS 2005 A Comparison of Missing Data Handling Methods Catherine Truxillo source 20
WUSS 2005 A Comparison of Two Procedures to Fit Multi-Level Data: PROC GLM versus PROC MIXED MaryAnne DePesquo Hope source 7
WUSS 2005 Graphing the Probability of Event as a Function of Time Using Survivor Function Estimates and the SAS System's PROC PHREG Tyler C. Smith,
Besa Smith		 source 18
WUSS 2005 Introducing the GLIMMIX Procedure for Generalized Linear Mixed Models Oliver Schabenberger source 20
NESUG 2005 Introducing the GLIMMIX Procedure for Generalized Linear Mixed Models Oliver Schabenberger 20
NESUG 2005 Introduction to SAS Enterprise Guide 3.0 for Statistical Analysis Charles B. Hallahan,
Linda P. Atkinson		 20
NESUG 2005 Logistic Regression: Ordinal and Nominal Outcomes Peter L. Flom 9
NESUG 2005 Using SAS for Cointegration and Error Correction Mechanism Approaches: Estimating a Capital Asset Pricing Model for House Price Returns Ismail E. Mohamed,
Theresa R. DiVenti		 14
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 Imputation of Categorical Variables with PROC MI Paul D. Allison source 14
SUGI 2005 Introducing the GLIMMIX Procedure for Generalized Linear Mixed Models Oliver Schabenberger source 20
SUGI 2005 Introduction to SAS Enterprise Guide 3.0 for Statistical Analysis Charles B. Hallahan,
Linda P. Atkinson		 source 20
SUGI 2005 IRT-FIT: SAS Macros for Fitting Item Response Theory (IRT) Models Robert Terry,
Sung-Hyuck Lee		 source 9
SUGI 2005 Maximum Likelihood Parameter Estimation with Incomplete Data Catherine Truxillo source 19
SUGI 2005 Mining Transactional And Time Series Data Michael J. Leonard,
Brenda Wolfe		 source 26
SUGI 2005 Single Event Timing Model with Heterogeneity: Predicting the Time of the First Home Purchase by Immigrants Eugene Brusilovskiy source 9
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 Introduction to Using Enterprise Guide for Statistical Analysis Charles B. Hallahan,
Linda P. Atkinson		 19
NESUG 2004 The Piecewise Regression Model as a Response Modeling Tool Eugene Brusilovskiy 10
SESUG 2004 Mixed Model Influence Diagnostics Oliver Schabenberger source 17
WUSS 2004 A SAS Recent Analysis of the Us Stock Market Performance Kamal Shoukry source 6
WUSS 2004 Are Religious Universities Religious?: A Multiple Regression Analysis of Varying Factors at Loyola Marymount University using SAS/ETS Procedures Jonathan Bingham,
Joel Shackelford		 source 11
WUSS 2004 Mixed Model Influence Diagnostics Oliver Schabenberger source 17
WUSS 2004 Package, Archive, Report and Test Statistical Models Using ODS Ted Clay source 10
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 An Experiment with Experimental Proc RobustReg Shuang Lu 5
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 Introduction to Using SAS Enterprise Guide for Statistical Analysis Charles B. Hallahan,
Linda P. Atkinson		 source 20
SUGI 2004 Mixed Model Influence Diagnostics Oliver Schabenberger source 18
SUGI 2004 Model-Based Multiple Imputation Geoffrey Paulin,
Shirley Tsai,
Melissa Grance		 source 13
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 Repeated Measures Modeling with PROC MIXED E. Barry Moser source 20
SUGI 2004 Some Statistical Strategies for Analyzing Confirmatory Studies Involving One or More Occurrences of Primary Events Gary G. Koch,
Maura E. Stokes		 source 21
WUSS 2003 Getting Started with PROC LOGISTIC Andrew H. Karp source 6
WUSS 2003 Investigating the Dynamics of Occupational Prestige Preferences Using SAS Statistical Procedures Using the SAS? System Kacey Lock,
Joseph E. Earley		 source 3
WUSS 2003 Regression Diagnostic Plots George C. J. Fernandez source 9
NESUG 2003 Routine Web Reporting With Simple SAS ODS Ashley Sanders 6
NESUG 2003 Solving Computable General Equilibrium Models with SAS Ban Cheah 12
NESUG 2003 Statistics & Regression - Easier than SAS Vincent Maffei,
Michael L. Davis		 6
SUGI 2003 Teaching Statistical Methods Courses with Case Studies and JMP Andy Mauromoustakos source 6
MWSUG 2002 A Macro to Assess the Key Drivers of Overall Product Acceptance using SAS System George J. Hurley,
David Hengehold		 7
NESUG 2002 Practice of SAS Logistic Regression on Binary Pharmacodynamic Data - Problems and Solutions Alan Xiao 5
SESUG 2002 Analysis of Dosage-Response Data in Agricultural Research K. Bondari source 6
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
WUSS 2002 Survival Analysis with PHREG: Using MI and MIANALYZE to Accommodate Missing Data Arthur L. Carpenter source 6
SUGI 2002 A Proportional Odds/Hazards Approach to Analyzing Likert Scale Data Lynette K. Duncan,
James E. Dunn		 source 5
SUGI 2002 Communicating the Results of Predictive Models to Non-technical Audiences Andrew H. Karp source 4
SUGI 2002 Individual Growth Analysis Using PROC MIXED Maribeth H. Johnson source 7
SUGI 2002 Redesigning Experiments with Polychotomous Logistic Regression: A Power Computation Application Charles M. Vaughan,
Serge Guzy		 source 6
SUGI 2002 Robust Regression and Outlier Detection with the ROBUSTREG Procedure Colin Chen source 13
SUGI 2002 SEM for Health, Business, and Education Diana D. Suhr source 8
NESUG 2001 Fast and Easy Ways to Annoy a Statistician: The Sharing and Presentation of Data Between a SAS Programmer and a Statistician Richard M. Mitchell 10
NESUG 2001 Using Surveys to Understand the Present and Predict the Future Aliza Heching,
Ying Tat Leung		 6
VIEWS 2001 A Conjoint-based Choice Modelling Approach Using the PHREG Procedure to Evaluate the Importance of Fisheries Management Objectives Premachandra Wattage,
Simon Mardle,
Sean Pascoe		 14
WUSS 2001 PROC GLM or PROC CALIS? Diana D. Suhr source 5
SESUG 2001 GETTING STARTED WITH PROC LOGISTIC Andrew H. Karp source 5
SESUG 2001 Individual Growth Analysis Using PROC MIXED Maribeth H. Johnson source 7
SCSUG 2001 Getting Started with PROC LOGISTIC Andrew H. Karp 5
SCSUG 2001 Individual Growth Analysis Using PROC MIXED Maribeth H. Johnson 7
SCSUG 2001 Using the SAS System to Demonstrate the Equivalence of On-line and On-Papeer Survey Adminstration across Levels of Raters Jim Penny 5
SCSUG 2001 Using the SAS System to Study the Gender and Level Measurement Equivalence of a Multi-rater Survey Jim Penny 6
SEUGI 2001 Web clickstream analysis to understand customer behaviour [presentation] Erika Blanc,
Paolo Giudici		 source 21
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
SUGI 2001 A Non-mathematical Introduction to Regression Concepts Using PROC REG Mel Widawski source 7
SUGI 2001 A SAS/IML Macro for Goodness-of-Fit Testing in Logistic Regression Models With Sparse Data Oliver Kuss source 5
SUGI 2001 Analysis of Count Data Using SAS Alexander Pedan source 6
SUGI 2001 Efficient Statistical Programming? - Let SAS Do the Work Keiko I. Powers source 4
SUGI 2001 Getting Started with PROC LOGISTIC Andrew H. Karp source 5
SUGI 2001 New Methods for Modeling Reliability Using Degradation Data Jose G. Ramirez,
Gordon Johnston		 source 7
SUGI 2001 PROC GLM or PROC CALIS? Diana D. Suhr source 3
SUGI 2001 Using SAS/IML Software for Solving Non-Standard Optimization Problems in Growth Modeling and Optimal Design Inna Perevozskaya source 6
SCSUG 2000 Multi-Level Intervention Study Data and PROC MIXED Tom Bohman 13
SESUG 2000 Performing Exact Logistic Regression with the SAS R /AD System Robert E. Derr source 10
NESUG 2000 A Pragmatic Intent-to-Treat Analysis Using SAS Patricia R. Houck,
Sati Mazumdar,
Kenneth S. Liu,
Charles F. Reynolds III		 5
NESUG 2000 Getting Started with PROC LOGISTIC Andrew H. Karp 5
NESUG 2000 Methods for the Analysis of Clustered Ordinal Response Data Robert J. Gallop,
J. Richard Landis,
Thomas R. Ten Have		 7
WUSS 2000 A Non-mathematical Introduction to Regression Using PROC REG Mel Widawski source 6
WUSS 2000 Detecting Curvillnear Relationships in PROC REG Mel Widawski source 9
WUSS 2000 Getting Started with PROC LOGISTIC Andrew H. Karp source 5
WUSS 2000 PROC CALIS Multi-Sample Analysis Diana D. Suhr source 3
WUSS 2000 SAS STAT applications in Econometrics Mathura Thillainathan,
George C. J. Fernandez		 source 10
SEUGI 2000 Forecasting Bad Debt by ARIMA Models with Multiple Transfer Functions using a Selection Process for many Candidate Variables [presentation] Alastair Jones,
Derek Hull,
John Adam		 source 18
PharmaSUG 2000 An Alternative to the Odds Ratio: A Method for Comparing Adjusted Treatment Group Effects on a Dichotomous Outcome P. Chris Holland 5
PharmaSUG 2000 Meta-Analysis with Linear and Nonlinear Multilevel Models Using PROC MIXED and PROC NLMIXED Eugene Komaroff,
Russell D. Wolfinger		 4
SUGI 2000 Detecting Curvilinear Relationships in PROC REG Mel Widawski source 9
SUGI 2000 Getting Started with PROC LOGISTIC Andrew H. Karp source 5
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 Multiple Imputation for Missing Data: Concepts and New Development Yang Yuan source 10
SUGI 2000 Performing Exact Logistic Regression with the SAS System Bob Derr source 10
SUGI 2000 Product Development and Applied Research: A Formal Approach Using SAS and JMP Software John A. Wass source 5
SESUG 1999 Analysis of Longitudinal Data: Comparison between PROC GLM and PROC MIXED Maribeth H. Johnson 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 Investigating Seasonality in BLS Data Using PROC ARIMA Joseph E. Earley source 6
NESUG 1999 Fitting Nonlinear Mixed Models with the New NLMIXED Procedure Russell D. Wolfinger 10
MWSUG 1999 Longitudinal Data Analysis Repeated-Measure ANOVA and Mixed Models Nancy E. Briggs,
Ching-Fan Sheu		 6
MWSUG 1999 REG, GLM, ANOVA: Which One? Why? How? Linda M. Quinn 6
SUGI 1999 A SAS Macro to Analyze Data from a Matched or Finely Stratified Case-Control Design Robert A. Vierkant,
Terry M. Therneau,
Jon L. Kosanke,
James M. Naessens		 source 6
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 Nonlinear Mixed Models with the New NLMIXED Procedure Russell D. Wolfinger source 10
SUGI 1999 Simplification on Learning Model by Using PROC GENMOD Kuolung Hu,
David Mckinzie,
Karen Nowak		 source 6
SUGI 1999 Study Design with SAS: Estimating Power with Monte Carlo Methods Robert W. Graebner source 3
MWSUG 1998 An Introduction to Binary Logistic Regression Linda M. Quinn 8
MWSUG 1998 If There Is A Will, There Is A Way: Getting Around Defaults of PROC LOGISTIC Chao-Ying Joanne Peng,
Tak-Shing Harry So		 10
WUSS 1998 Getting Started with PROC LOGISTIC Andrew H. Karp source 5
WUSS 1998 Which Path with PROC CALIS? Diana D. Suhr source 7
NESUG 1998 A Simulation Study of Estimators In Stratified Proportional Hazard Models Hsi-Wen Liao 8
NESUG 1998 Calculating Marginal Probabilities in PROC PROBIT Guy Pascale 5
NESUG 1998 Risk Evaluation after Heart Valve Replacement by PROC PHREG Choa Chen 7
PNWSUG 1998 Parameter Evaluation and Statistical Validation of Transport Parameters in Porous Media Mahesh A. Rege,
David R. Mills,
James N. Peterson,
Yunwei Sun,
David R. Yonge,
Donald L. Johnstone,
William A. Apel		 9
SUGI 1998 Finding the Solution to Data Mining: A Map of the Features and Components of SAS Enterprise Miner Software Table of Contents John C. Brocklebank,
Mark Brown		 source 24
SUGI 1998 Overall Part Number Item Rank Rank source 19
SUGI 1998 Reporting Results of Multiple Logistic Regression Models Depending on the A vailability of Data Richard M. Mitchell source 5
SUGI 1998 Robust Standard Error Estimate for Cluster Sampling Data: A SAS/IML Macro Procedure for Logistic Regression with Huberization Honghu Liu source 6
SCSUG 1997 Reliability Data Analysis in the SAS System Gordon Johnston 10
WUSS 1997 Analysis of Time Series Data - An Application in Health Care Sujaya Parthasarathy source 6
WUSS 1997 Confirmatory Factor Analysis Using PROC CALIS Diana D. Suhr,
James Keaton,
Lynne Kelly,
Cynthia Finch		 source 5
WUSS 1997 Logistic Regression Modeling in Complex Surveys: Examples Using LOGITSE SAS Macro Jesse Albert Canchola,
Brian D. Marx,
Joseph A. Catania		 source 10
WUSS 1997 Reliability Data Analysis in the SAS System Donna O. Fulenwider,
Gordon Johnson		 source 10
WUSS 1997 The Sums of Squares Are All the Same - How Can the LSMEANS Be So Different? Lori Potter,
David J. Pasta		 source 6
WUSS 1997 Using SAS Multivariate Procedures to Estimate Human Development Indicators: The Case of Education and Human Development Joseph E. Earley source 4
NESUG 1997 Using Logistic Regression to Test for Interaction in the Presence of Zero Cells Lisa Suchower 10
MWSUG 1997 Analysis of Covariance: A Useful Tool For Investigating Molecular Interaction John A. Wass 3
MWSUG 1997 Reliability Data Analysis in the SAS System Gordon Johnston 10
SESUG 1997 Computer-Assisted Real-Time Observation: Issues in Data Management Eric V. Bodner,
Michael J. Demand		 2
SESUG 1997 Summarization of LOGISTIC Regression Results When There Are Many Dependent Variables and a Common Shared Set of Explanatory Variables John T. Jones 7
PharmaSUG 1997 Visual Component Analysis: Interactive Graphical Modeling in SAS and ViSta/XLispStat Richard A. Faldowski 13
SUGI 1997 Forecasting College Enrollment Using the SAS System Joseph E. Earley,
Archie J. Calise		 source 4
SUGI 1997 Getting Started with PROC LOGISTIC Andrew H. Karp source 5
SUGI 1997 Introduction to Building a Linear Regression Model Leslie A. Christensen source 7
SUGI 1997 Regional Theatre: Statistical Reflections on the Bottom Line James D. Ryan source 7
SUGI 1997 The Tobit Model: An Example of Maximum Likelihood Estimation with SAS/IML Charles B. Hallahan source 6
SUGI 1997 Using Linear Regression and the Gibbs Sampler to Estimate the Probability of a Part Being Within Specification Brenda Cantell source 6
SCSUG 1996 Getting Started with PROC LOGISTIC Andrew H. Karp 5
SESUG 1996 Getting Started with PROC LOGISTIC Andrew H. Karp 5
NESUG 1996 Maximum Likelihood Estimation with SAS/IML Charles B. Hallahan 7
WUSS 1996 Repeated Measures Analysis with the SAS System Kathleen Kierman source 10
SUGI 1996 A Study of Kinetics: The Estimation and Simulation of Systems of First Order Differential Equations Donald Erdman,
Maurice M. Morelock		 source 8
SUGI 1996 A Tutorial on Bootstrapping in the SAS System Paul A. Thompson source 10
SUGI 1996 Analysis of Unbalanced Mixed Model Data Ramon C. Littell source 6
SUGI 1996 Tips on JMPing into Mixture Experimentation Daniel J. Obermiller source 6
SUGI 1996 Using PROC ARIMA to Test an Intervention Effect Neil S. Fleming,
Eric Gibson,
David G. Fleming		 source 10
SUGI 1996 Using SASlETS Software to Develop a Forecasting Model Barbara Ledwith-Crosby source 4
MWSUG 1995 An Introduction to Binary Logistic Regression Linda M. Quinn 8
MWSUG 1995 Applications of PROC PHREG Enhancements in Version 6.10 Ying C. So 9
MWSUG 1995 Hypothesis Testing & Confidence Interval Estimation via the Least Absolute Value (LAV) Approach Tom G. Filloon 6
NESUG 1995 Estimating MEXVAL Statistics Ashok Mehta 5
NESUG 1995 Getting Started with PROC LOGISTIC Andrew H. Karp 5
NESUG 1995 Multiple Minima: Phenomena of The Data Or A Drawback Method? (Comparison of SAS/IML NonLinear Optimization Routines) Ekaterina Gibiansky 4
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 Heteroskedasticity in Regression Model - Detection and Remedial Measures Using SAS 6.10 George C. J. Fernandez source 10
SESUG 1995 Getting Started with PROC LOGISTIC Andrew H. Karp 5
SESUG 1995 Information Visualization STATISTICAL GRAPmCS David A. Dickey 6
SESUG 1995 Intraclass Correlation Reliability Estimation Using the GLM and MIXED Procedures Maribeth H. Johnson 5
SUGI 1995 A Comparative Evaluation of Selected Statistical Software for Computing Various Categorical Analyses Nancy McDermott,
Cynthia White		 source 6
SUGI 1995 A Primer on Poisson Regression using SAS/STAT Software Methods and Interpretation of Results Richard McNally source 4
SUGI 1995 Modeling Variation in Repeated Measures Data Ramon C. Littell source 5
SUGI 1995 Robust Analysis Adds M-uscle to Data Analyses E. Charlene Drago,
Tom Filloon		 source 6
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
WUSS 1994 SAS in Taming Classical Violations Kamal Shoukry source 3
MWSUG 1994 Alternative Approaches to Mixed Linear Models George W. Pasdirtz 6
SESUG 1994 Managing Overkill: How to Use SAS PROC CA TMOD to Estimate Odds Ratios Sigurd W. Hermansen 5
SESUG 1994 rOSTERS Applications in SASIIMLTM: Getting Odds Ratios from PROC LOGISTIC D. Kim Chantala 5
SEUGI 1994 Analysis of Dose-response Curves in Molecular Pharmacology by the SAS System Paola Baiardi source 10
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 Computing Case Diagnostics for Structural Equation Models Noel G. Cadigan source 5
SUGI 1994 Mixed Model Analysis of Data: Transition from GLM to MIXED Ramon C. Littell source 8
SUGI 1994 Programming the NUN Procedure Using the Negative Binomial Yield Model for ASIC Semiconductors Jon A. Patrick source 4
WUSS 1993 A SAS Macro to Test the Significance of Differences Between Parameter Estimates in PROC CATMOD Linda R. Ferguson,
Mel Widawski,
Dawn M. Upchurch		 source 5
MWSUG 1993 Data Ansalysis Semicolon-Free: Using SAS without the Syntax Julia Brooks 3
SEUGI 1993 A New Look at the Facilities in PROC MIXED James L. Roger source 12
SEUGI 1993 Simulation Models for Business Planning and Economic Forecasting Liza Evans source 7
SEUGI 1993 Variable Selection Techniques Implemented in Procedures of SAS Software Olaf Gefeller source 9
SUGI 1993 A SAS Macro Procedure to Summarize the Output of Logistic Regression Models Benjamin I. Broder,
Chih-Ping Chou		 source 6
SUGI 1993 Generating Confidence in the SAS System: Confidence Intervals for Commonly Used Procedures Jose Maria J. Alvir source 4
SUGI 1993 SAS Software to Fit the Generalized Linear Model Gordon Johnston source 8
SUGI 1993 Simulation Models for Business Planning and Economic Forecasting Donald Erdman source 7
SUGI 1993 Using SAS/ETS in Applied Econometrics: Parameter Estimates for the CES-Translog Specification John J. Hisnanick source 5
SESUG 1993 Repeated Measures Using PROC MIXED Instead of PROC GLM James H. Roger,
Michael Kenward		 10
NESUG 1992 An In-Depth Look at the PHREG Procedures Peter P. Gaccione 9
SEUGI 1992 Using SAS Macros and PROC IML to Create Special Designs for Use in Generalised Linear Models John Hendrickx source 22
SUGI 1992 An Alternative Convergence Criterion for the NLIN Procedure William Potts source 4
SUGI 1992 Analysis of Incomplete Categorical Repeated Measures Charles S. Davis source 6
SUGI 1992 Graphical Aids for Summarizing Inferential Results of Nonlinear Regression William J. Price,
Bahman Shafii		 source 6
SUGI 1992 Influence Measures in Nonlinear Regression Tapon Roy source 4
SUGI 1992 INSIGHT into Multiple Regression Robert A. Muenchen source 4
SUGI 1992 The Investigation of Suicide Using SAS Software Procedures: A SAS/ETS Approach Seid M. Zekavat source 6
SUGI 1992 Using the ARIMA Procedure in Forecasting the Demand and Utilization of Inpatient Hospital Services John J. Hisnanick source 9
SUGI 1992 Using the NLIN Procedure to Combine Estimates of Relative Potency Stan Altan,
Jaya Natarajan		 source 6
SEUGI 1991 Future Directions of Statistical Software with the SAS System David M. DeLong source 20
SEUGI 1991 Statistical Evaluation and Forecasting of Steel Corrosion Data Bernhard Kienzler,
Emanuel Smailos,
Rainer Koester		 source 11
SUGI 1991 A Program to Compute Odds Ratios and Confidence Intervals from LOGISTIC Output Eric Yu I. Wang,
Aili Gong,
David P. MacKinnon		 source 4
SUGI 1991 Econometric Modeling of Sweetgum Stem Biomass Using the IML and SYSLIN Procedures Bernard R. Parresol,
Charles E. Thomas		 source 6
SUGI 1991 Fitting Sums of Exponentials Using the Method of Residuals and the NLIN Procedure in SAS Software Gail Butler source 6
SUGI 1991 Power Analysis and Instructional Monte Carlo Simulations Richard W. Cole source 4
SUGI 1991 SAS/ETS Software in Applied Econometrics: Evaluating Input Separability in a Model of the U.S. Manufacturing Sector John J. Hisnanick source 6
SEUGI 1990 Performing Conjoint Analysis Using Proc Transreg Bjarne Nielsen,
Marcus Schmidt		 source 6
SUGI 1990 Alternative Parameterization for Anova Models Using SAS Software Robert M. Hamer source 8
SUGI 1990 ANALYSIS OF COVARIANCE: REPEATED IfEASURES AND SPLIT-Plur DESIGNS George A. Milliken source 10
SUGI 1990 Determining Weight Values for EWMA Control Schemes Using the ARIMA Procedure John C. Brocklebank source 10
SUGI 1990 Estimating Standard Errors for a Proposed Survey Samuel M. Slowinski,
Hank Leddon		 source 6
SUGI 1990 The GLIM Procedure: An Interface to the SAS System P. M. Grambsch,
Jon L. Kosanke,
Terry M. Therneau,
D. J. Schaid,
R. Zinsmeister,
H.S. Wieand,
Kenneth P. Offord,
J. J. LarsonKeller		 source 5
SEUGI 1989 A Bioassay Method Using SAS/STAT Software C. M Fenton,
P. Blood		 source 12
SUGI 1989 A SAS/IML Matrix Program to Estimate Indirect Effects and Their Standard Errors David P. MacKinnon,
Eric Yu I. Wang		 source 6
SUGI 1989 Estimating the Translog Functional Form and Calculating Elasticities with Standard Errors: An Application of the IML Procedure Gary S. Klonicki source 6
SUGI 1989 Examining the Relationship between Survival Time and Time-dependent Covariables Using the PHSPLM Procedure Frank E. Harrell Jr.,
James E. Herndon II		 source 6
SUGI 1989 How to Establish a Forecasting System with SASSoftware Joel Fingerman source 10
SUGI 1989 The PHGLM Procedure for Time-Dependent Covariates - and the Case-Cohort Design David Yu-Wu Pee,
Sholom Wacholder		 source 6
SEUGI 1988 Confidence Regions for Non-Linear Regression Graham Healy source 8
SUGI 1988 A Multivariate Approach to Social Inequality Martin G. Ribe source 6
SUGI 1988 Regression and the SAS System: An Overview Rudolf J. Freund source 9
SEUGI 1987 Tutorial on PROC REG Gerhard Held source 39
SUGI 1987 Application of Intervention Analysis to Power Plant Monitoring Data Linda E. Bireley source 9
SUGI 1987 Maximum Likelihood Estimation and Simulation for One and Two Stage Sampling of Normal Mixtures Using SAS Software Kirby Jackson,
Wesley Kemmerlin		 source 4
SUGI 1987 The Analysis of Survival Data with Concomitant Information using Parametric Models: PROC HAZARD and PROC HAZPRED Eugene H. Blackstone,
David C. Naftel		 source 6
SUGI 1987 The Bayesian Estimation of Linear Models: An Application of the Lindley-Smith Hyperparameter Model Dennis J. Aigner,
Joseph G. Hirschberg		 source 6
SEUGI 1986 Generalized Linear Models in SAS Using PROC GLM James Roger source 10
SEUGI 1986 SAS/STAT Software on the IBM PC under PC DOS Gerhard Held source 12
SUGI 1986 Comparing Parameter Estimates Between Linear Models John E. Teberg source 7
SUGI 1986 Performing the X1 1ARIMA Seasonal Adjustment John C. Brocklebank,
David A. Dickey		 source 10
SUGI 1986 Repeated Application of a Generalized Logistic Model To Count Data Using PROC MATRIX Linda Williams Pickle source 6
SUGI 1986 Using PROC NLIN for Time Series Prediction Wayne Fuller source 6
SUGI 1985 A SAS Macro for Logistic Discrimination for Three or More Populations James E. Dunn,
Eileen C. King		 source 6
SUGI 1985 PROC PECAN - A SAS Procedure Sivaram Kalyandrug,
Jay H. Lubin		 source 8
SEUGI 1984 New Statistical Features in SAS Gerhard Held source 13
SUGI 1984 A Macro for Fitting Nonlinear Models to Poisson Distributed Data Edward L. Frome,
Richard W. McLain		 source 6
SUGI 1984 Changes and Enhancements to SAS/ETS Procedures David M. DeLong,
Leigh A. Ihnen,
Mark Little		 source 6
SUGI 1983 A Macro for Maximum Likelihood Fitting Log-Linear Models to Poisson and Multinomial Counts with Contrast Matrix Capability for Hypothesis Testing Gary G. Koch,
Maura E. Stokes		 source 6
SUGI 1983 Evaluation of Non-accelerated Stability Data Kathleen Karpenter Dietrich,
Daniel L. Weiner		 source 6
SUGI 1983 Missing Events in Survival Analysis Peter A. Lachenbruch,
Robert F. Woolson		 source 6
SUGI 1983 PROC DISCRETE-A Procedure for Fitting Discrete Probability Distributions Charles E. Gates,
James P. Geaghan,
George D. Williams		 source 4
SUGI 1983 PROC MATRIX Macros for the Generalized Incomplete Model (GIM) and for the Multiple Design Matrix Model (MDM) Diane Fairclough,
Ronald W. Helms		 source 6
SUGI 1983 Regression of Simultaneous Systems Subject to Highly Nonlinear Constraints William Alexander,
C. Richard Shumway,
Hovav Talpaz		 source 6
SUGI 1982 A Pharmacokinetic Analysis System (PAS) Raymond P. Chen,
Daniel M. Wildman		 source
SUGI 1982 Applications of SAS (FUNCAT) to the Analysis of Epidemiological/Survivorship Data Saeid B. Amini,
William R. Clarke,
Robert F. Woolson		 source 9
SUGI 1982 Estimation of a Translog Cost Function Using SAS George M. McCollister source 3
SUGI 1982 Linear Models with Dominant Variables Peter S. Lufkin source 6
SUGI 1981 Estimating the Parameters of the Michaelis-Menten Equation Using SAS Thomas P. Capizzi,
Leonard Oppenheimer		 source 6
SUGI 1981 Parameter Estimation, Hypothesis Testing and Coding Chip Kaliher source
SUGI 1981 Using PROC G3D for Visualization of the Contour Plot of Residual Sums of Squares in PROC NLIN Derrick J. Bates source 4
SUGI 1980 Examples of GLM Applications Ramon C. Littell source 7
SUGI 1979 An Evaluation of Nonlinear Regression Programs C. M. Metzler source 9
SUGI 1979 Using GLMM5 for General Linear Models Analysis - A Tutorial II. Three Examples Imogene McCanless,
Ronald W. Helms		 source 9

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