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maximum likelihood estimation

413 papers and 6 presentations; 382 titles.

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Conference × Year × Title × Authors Extras Pages
WUSS 2026 The GENMOD Toolkit: What do you do when things aren't Normal? [presentation] Danny R. Modlin source 36
WUSS 2026 The Living Dead in Your Cohort: Immortal Time Bias Detection and Correction in SAS Mehrnaz Siavoshi source 14
PharmaSUG CN 2026 Handling Missing Data in Analgesia Clinical Trials and Corresponding SAS Implementation Jingbo Zhu,
Jiehan Zhang		 source 17
PHUSE US 2026 Demystifying TMLE: A Practical Approach for Clinical Data Scientists Joshua Enxing source
presentation source		 12
PHUSE APAC 2026 Estimation of the Hypothetical Estimands using Longitudinal version of the TMLE Shreya Wahi source
presentation source		 8
PHUSE APAC 2026 Targeted Maximum Likelihood Estimation: A Unified Approach for Confounding and Selection Bias Mahjoob O. Majeed,
Noel S. John		 source
presentation source		 6
MWSUG 2025 Conducting Survival Analysis in SAS using Medicare Claims as a Real-world data source Jayanth Iyengar source 32
MWSUG 2025 Logistic Regression Odyssey on a Small Sample Due to Rare Cancer [presentation] Brandy R. Sinco,
Jessie Dalman,
Tasha Hughes		 source 46
SESUG 2025 The GENMOD Toolkit: What do you do when things aren't Normal? Danny R. Modlin 36
WUSS 2025 Conducting Survival Analysis in SAS using Medicare Claims as a Real-world data source Jayanth Iyengar source 32
WUSS 2025 The GENMOD Toolkit: What do you do when things aren't Normal? [presentation] Danny R. Modlin source 36
PharmaSUG 2025 Conducting Survival Analysis in SAS using Medicare Claims as a Real-world data source Jayanth Iyengar source 32
PharmaSUG 2025 Super Learner for Predictive Modeling and Causal Analysis Honghe Zhao,
Clay Thompson,
Michael Lamm		 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 Integration of an R Language Function Within SAS to Perform Conditional Multivariate Saddlepoint Approximation Christopher Johnson source 8
WUSS 2024 Limit of Detection Calculation Methods Comparison for PCR-based Quantitative Studies using the SAS System Jesse Albert Canchola source 13
WUSS 2024 Matrices and More: An Overview of the SAS/IML Language [presentation] Rick Wicklin source 46
PharmaSUG 2024 Bayesian Methods in Survival Analysis: Enhancing Insights in Clinical Research Vadym Kalinichenko source 11
WUSS 2023 The Delta Method in Statistical Inference, with Applications in the SAS IML Procedure Carter Sevick,
Camille Moore,
Samantha MaWhinney		 source 14
PharmaSUG 2023 Fitting Logitoid-Normal distributions with MLE estimate by SAS SEVERITY and FCMP procedures Lili Huang,
Helen Dong,
Yuanyuan Liu		 source 8
PHUSE EU 2021 Transition Probability for Analysis of COVID Test Positivity Ra [presentation] Hrishikesh K S,
Limna Salim		 source
video		 10
SESUG 2021 Screening, Binning, Transforming Predictors for a Generalized Logit Model Bruce S. Lund source 17
PHUSE US 2021 Comparative Characteristics of Logistic Regression Implementation in SAS and R in the Example of Cardiovascular Diseases [presentation] Serhii Kashyn source
video		 22
PHUSE US 2021 Parmsurv: An SAS Macro for Flexible Parametric Survival Analysis with Long-term Predictions Han Fu,
Shahrul Mt-Isa		 source
video
presentation source		 10
SGF 2021 Reporting Correlation Coefficient Results and Plots: A SAS Macro That Does It All Zhengming Chen,
Bowen Zheng		 source
presentation		 11
SGF 2021 Weight of Evidence, Dummy Variables and Degrees of Freedom Bruce S. Lund source
sas
presentation
pdf		 15
PHUSE EU 2020 MI FOR MI, OR HOW TO HANDLE MISSING INFORMATION WITH MULTIPLE IMPUTATION Daria Shamaida source
video
presentation source		 8
SGF 2020 Analyzing Non-normal Data: Application to Missing Data Problems Niloofar Ramezani source 10
SGF 2020 Don't Just Survive, Thrive with This Multi-Stratified Cox Proportional Hazards Model Macro Katelyn J. Ware,
Paul Egeler		 source 11
SGF 2020 Is it possible to reduce smoking by increasing taxes? An analysis on Danish data using SAS software Anders Milhøj source 13
SGF 2020 Modeling of Between - and Within-Subject Variances using Mixed Effects Location Scale (MELS) Models Qianheng Ma,
Donald Hedeker		 source 14
SGF 2020 Multinomial vs. Ordinal. Does model selection make a difference? for SAS Global Forum 2020 Corey Leadbeater source 15
SGF 2020 Using Analytics to Predict Tax Recovery and Prioritize Audits and Investigations in Canada Jason A. Oliver source 19
PharmaSUG 2020 Gradient Descent: Using SAS for Gradient Boosting Karen Walker source 11
PHUSE US 2020 Handling Missing Data in Clinical Trials: Techniques and Methods Pennidhi Karlakunta,
Naveen Kommuru		 source
presentation source		 9
SESUG 2019 Advanced Statistical Modeling within Machine Learning and Big Data Analytics Niloofar Ramezani,
George Mason		 source 16
SESUG 2019 Glass Box Neural Networks Ross Bettinger source 14
SESUG 2019 The Best of Both Worlds: Forecasting Using Time Series with Inputs David A. Dickey source 19
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
WUSS 2019 Limit of Detection (LoD) Estimation Using Maximum Likelihood from (Hit) Rate Data: The LoD_MLE SAS Macro Jesse Albert Canchola,
Jeffrey E. Vaks,
Shaowu Tang		 source 11
SGF 2019 IFRS9: Using SAS/ETD Software and SAS Studio to Select Macro Economic Variables Julio Alberto Campa Vega Filho source 19
SGF 2019 Predicting Patients at High Risk of Hospital-Acquired Conditions Using the LOGISTIC Procedure Jennifer Hargrove,
Pamela Hipp,
Glenn Sidle		 source 12
SGF 2019 Survival Estimates Prediction with Survey Data Bocheng Jing,
L. Grisell Diaz-Ramirez,
W. John Boscardin,
Alexandra K. Lee,
Sei J. Lee		 source 12
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 Zero-Inflated and Zero-Truncated Count Data Models with the NLMIXED Procedure Robin High source 18
PHUSE EU 2018 Forest Plots in Survival Subgroup Analyses Michael Brockmann,
Julia Benzing		 source
presentation source		 11
SESUG 2018 Forecasting: Something Old, Something New David A. Dickey source 26
MWSUG 2018 Application of heavy-tailed distributions using PROC IML, NLMIXED and SEVERITY Palash Sharma 14
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 Handling Missing Data in Exploratory Factor Analysis Using SAS Min Chen 3
WUSS 2018 Forecasting tourist's arrivals to the USA with SARIMA models. Mostafa Zahedjahromi source 9
WUSS 2018 Forecasting: Something Old, Something New David A. Dickey source 26
WUSS 2018 Using PROC MCMC in a Process Control Setting: An Illustrative Example with PROC IML Austin R. Brown source 8
PHUSE US 2018 Missing Data Imputation and Its Effect on the Accuracy of Classification Edwin Ponraj Thangarajan,
Giri Balasubramanian		 source
presentation source		 15
SGF 2018 Alternative Variance Parameterizations in Count Data Models Robin High source 14
SGF 2018 Confirmatory Factor Analysis in SAS : Application to Public Administration Niloofar Ramezani source 13
SGF 2018 Forecasting: Something Old, Something New David A. Dickey 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 Model Selection Using Information Criteria (Made Easy in SAS ) Wendy Christensen source 12
SGF 2018 Penalized Variable Selection and Quantile Regression in SAS : An Overview Russell M. Lavery source 28
SGF 2018 Using the IML Procedure to Examine the Efficacy of a New Control Charting Technique Austin R. Brown source 8
SESUG 2017 Applying Logistics Regression to Forecast Annual Organizational Retirements Alan Dunham source 12
MWSUG 2017 Correcting for Selection Bias in a Clinical Trial Shana Kelly 8
MWSUG 2017 Correlation and Structural Equation Analysis on the Effects of Anti-Discrimination Policies and Resources on the Well Being of Lesbian, Gay, and Bisexual College Students Brandy R. Sinco,
Michael Woodford,
Jun Sung Hong,
Jill Chonody		 22
MWSUG 2017 Logistic Model Selection with SAS PROC's LOGISTIC, HPLOGISTIC, HPGENSELECT Bruce S. Lund 18
MWSUG 2017 Unconventional Statistical Models with the NLMIXED Procedure Robin High 14
WUSS 2017 Examining the Performance of a Control Chart for the Shifted Exponential Distribution using Penalized Maximum Likelihood Estimators: A Simulation Study using SAS Austin R. Brown,
Bryce Whitehead		 source 8
PharmaSUG 2017 Survival 101 - Just Learning to Survive Leanne Goldstein,
Rebecca Ottesen		 source 20
SGF 2017 %SURVEYGENMOD Macro: An Alternative to Deal with Complex Survey Design for the GENMOD Procedure Alan Ricardo da Silva source 28
SGF 2017 An Investigation into Big Data Analytics Applied to Insurance Rebecca Peters,
Penny Holborn		 source 18
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
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
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 To be two or not be two, that is a LOGISTIC question Robert G. Downer 10
WUSS 2016 Introduction to Survival Analysis in SAS Leanne Goldstein,
Rebecca Ottesen		 source 19
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 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 Applying Frequentist and Bayesian Logistic Regression to MOOC data in SAS: a Case Study Yan Zhang,
Ryan Baker,
Yoav Bergner		 source
presentation		 7
SGF 2016 Correcting the Quasi-complete Separation Issue in Logistic Regression Models Xinghe Lu source 10
SGF 2016 Multiple-Group Multiple Imputation: An Empirical Comparison of Parameter Recovery in the Presence of Missing Data using SAS Patricia Rodríguez de Gil,
Jeffrey D. Kromrey		 source 15
SGF 2016 Using SAS to Conduct Multivariate Statistical Analysis in Educational Research: Exploratory Factor Analysis and Confirmatory Factor Analysis Jun Xu,
Steven L. Holtzman,
Kevin Petway,
Lili Yao		 source 13
SCSUG 2015 Using SAS Software to Determine the Mixed Rotterdam Demand Model Parameters and Test Statistical References Maryam Tabarestani,
Hector Zapata		 23
MWSUG 2015 Fitting and Evaluating Logistic Regression Models Bruce S. Lund 26
PHUSE EU 2015 How to Reduce Bias in the Estimates of Count Data Regression Ashwini Joshi,
Sumit Singh		 source
presentation source		 10
SESUG 2015 A Macro for Calculating Percentiles on Left Censored Environmental Data using the Kaplan-Meier Method Dennis J. Beal,
Oak Ridge		 source 6
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 Introduction to SAS Quantile Regression (PROC QuantSelect and PROC QuantReg ) Peter L. Flom source 25
SGF 2015 Addressing AML Regulatory Pressures by Creating Customer Risk Rating Models with Ordinal Logistic Regression Edwin Rivera,
Jim West		 source 12
SGF 2015 Double Generalized Linear Models Using SAS: The %DOUBLEGLM Macro Paulo Silva,
Alan Ricardo da Silva		 source
zip		 16
SGF 2015 Imputing Missing Data using SAS Christopher Yim source 9
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 Selection and Transformation of Continuous Predictors for Logistic Regression Bruce S. Lund source 16
SGF 2015 Survival Analysis with Survey Data Joseph C. Gardiner source 17
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 Time Series Modeling and Forecasting--An Application to Stress-Test Banks Ania Supady source 13
SGF 2015 Using the SAS-PIRT Macro for Estimating the Parameters of Polytomous Items Sung-Hyuck Lee source 9
SGF 2015 Validation and Monitoring of PD Models for Low Default Portfolios Using PROC MCMC Machiel Kruger source 16
SCSUG 2014 Selection and Transformation of Continuous Predictors for Logistic Regression Bruce S. Lund 13
SESUG 2014 Don't be binary! Tales of Non-binary Categorical Regression Charlotte Baker source 6
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
SESUG 2014 Penalizing Your Models: An Overview of the Generalized Regression Platform Michael Crotty,
Clay Barker		 source 8
PHUSE EU 2014 Small Sample Bayesian Factor Analysis Dirk Heerweghm source
presentation source		 18
MWSUG 2014 Selection and Transformation of Continuous Predictors for Logistic Regression Bruce S. Lund 12
WUSS 2014 Options in Estimating Nonlinear Mixed Models: Quadrature points and Approximation Methods Nate Smith,
Shelley A. Blozis		 source 7
WUSS 2014 Using PROC FACTOR for variable inclusion in PROC SURVEYLOGISTIC: A Case Study Deanna Naomi Schreiber-Gregory source 35
PharmaSUG 2014 A Mental Health and Risk Behavior Analysis of American Youth Using PROC FACTOR and SURVEYLOGISTIC Deanna Naomi Schreiber-Gregory source 23
PharmaSUG 2014 Survival 101 - Just Learning to Survive Leanne Goldstein,
Rebecca Ottesen		 source 19
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 Mental Health and Risk Behavior Analysis of American Youth Using PROC FACTOR and SURVEYLOGISTIC Deanna Naomi Schreiber-Gregory 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 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 Association of Socio-Emotional Factors: Religious Affiliation, Depression to Suicidal Tendency Among Adolescent Girls Sesha Sai Ega,
Chandra Shekar Pulipati,
Venkata Rachapudi		 source 6
SGF 2014 Case-Level Residual Analysis in the CALIS Procedure Catherine Truxillo source 17
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 Regression Analysis of Duration and Severity Data: New Capabilities with SAS Software Joseph C. Gardiner source 19
SGF 2014 SAS/STAT 13.1 Round-Up Bob Rodriguez,
Maura E. Stokes		 source 25
WUSS 2013 A Tutorial on PROC LOGISTIC Arthur X. Li source 19
WUSS 2013 Survival 101 - Just Learning to Survive Leanne Goldstein,
Rebecca Ottesen		 source 24
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 Fit Discrete Distributions via SAS Macro Fit Discrete Distributions source 5
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 Bayesian Statistics: Concept and Bayesian Capabilities in SAS Mark Janssens source
presentation source		 15
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 Ideas and Examples in Generalized Linear Mixed Models David A. Dickey 12
PharmaSUG 2013 Time to Event Analysis in the Pharmaceutical and Medical Device Industries Helen M. Chmiel,
Evan L. Ritzema		 source 8
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 SAS Macro for Applying Multiple Imputation to Multilevel Data Stephen Mistler source 8
SGF 2013 Getting Started with the SAS/IML Language Rick Wicklin source 21
SGF 2013 Joint Modeling of Mixed Outcomes in Health Services Research Joseph C. Gardiner source 16
SGF 2013 Models for Ordinal Response Data Robin High source 16
SGF 2013 Ordinal Response Modeling with the LOGISTIC Procedure Bob Derr source 20
SGF 2013 Predicting Health Care Expenditures with the MCMC Procedure Gregory Watson source 12
NESUG 2012 Introducing the FMM Procedure for Finite Mixture Models Maura E. Stokes 22
PHUSE EU 2012 Estimating Terminal Half Life by Non-Compartmental Methods with Some Data Below the Limit of Quantification Jochen Müller-Cohrs source 6
PHUSE EU 2012 The Logic and Logistics of Logistic Regression, Including New Features in SAS 9.2 Lawrence Rasouliyan source
presentation source		 16
SESUG 2012 %MIXED_FIT: A SAS Macro to Assess Model Fit and Adequacy for Two-Level Linear Models Mihaela Ene source 8
MWSUG 2012 Modeling Complex Survey Data Taylor Lewis 16
MWSUG 2012 Models for Ordinal Response Data Robin High 11
MWSUG 2012 Survival of the Milkman - How Modern Analytics is Helping an Old Fashioned Business Thrive Bruce Bedford 13
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 Up To Speed With Categorical Data Analysis Maura E. Stokes source 25
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
SGF 2012 Beyond Binary Outcomes: PROC LOGISTIC to Model Ordinal and Nominal Dependent Variables Eric P. Elkin source 8
SGF 2012 Exploratory Factor Analysis with the World Values Survey Diana D. Suhr source 19
SGF 2012 Exploring the Dimensionality of Large-Scale Standardized Educational Assessments Using PROC FACTOR Jonathan Steinberg source 10
SGF 2012 Handling Missing Data by Maximum Likelihood Paul D. Allison source 21
SGF 2012 Introducing the FMM Procedure for Finite Mixture Models David Kessler,
Allen McDowell		 source 22
SGF 2012 Knowledge (of Your Missing Data) Is Power: Handling Missing Values in Your SAS Data Set Theresa Schwartz,
Rachel Zeig-Owens		 source 8
SGF 2012 Modeling Heavy-Tailed Distributions in Healthcare Utilization by Parametric and Bayesian Methods Joseph C. Gardiner source 15
SGF 2012 Your Survival Guide to Using Time-Dependent Covariates Melissa E. Bagnell,
Teresa M. Powell		 source 10
SCSUG 2011 SAS-Implementations Supporting Satellite, Aircraft, and Drone-based Remote Sensing Endeavors and Their Influences in the Classroom Cecil R. Hallum source 16
SESUG 2011 Analysis of a Binary Outcome Variable Using the FREQ and LOGISTIC Procedures Arthur X. Li source 18
SESUG 2011 Eyes on the Road: A Methodology for Analyzing Complex Eye-Tracking Data Eye Tracking source 11
SESUG 2011 On Deck: SAS/STAT 9.3 Maura E. Stokes,
Fang K. Chen		 source 20
SESUG 2011 Tailoring Logistic Regression Model Analyses with the ODDSRATIO Statement in PROC LOGISTIC Taylor Lewis source 8
SESUG 2011 Using SAS to Examine Aging Expectation (ERA-38) for Older Adults Abbas S. Tavakoli,
Julie Freelove-Charton		 source 8
WUSS 2011 On Deck: SAS/STAT 9.3 Maura E. Stokes source 20
WUSS 2011 Up To Speed With Categorical Data Analysis Maura E. Stokes source 25
MWSUG 2011 On Deck: SAS/STAT 9.3 Maura E. Stokes,
Fang K. Chen,
Ying So		 20
NESUG 2011 On Deck: SAS/STAT 9.3 Maura E. Stokes 20
PharmaSUG 2011 Evaluating Safety Signals in Clinical Trials: the Dirichlet-NBD Model Implementation with SAS Yuqin Li,
Xiaohai Wan		 source 7
SGF 2011 Logit Models in Practice: B, C, E, G, M, N, O, ... Joseph C. Gardiner,
Zhehui Luo		 source 20
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 SAS/ETS and the Nobel Prize David A. Dickey source 14
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
NESUG 2010 An Animated Guide: An introduction to Poisson Regression Russell M. Lavery 17
NESUG 2010 Exploring the Dimensionality of Large-Scale Standardized Educational Assessments Using PROC FACTOR Jonathan Steinberg 8
NESUG 2010 The Next Generation: SAS/STAT 9.22 Maura E. Stokes,
Robert N. Rodriguez,
Robert Cohen		 20
WUSS 2010 Dummy Coding for Dummies Kathryn Martin source 10
WUSS 2010 The Next Generation: SAS/STAT 9.22 Robert N. Rodriguez source 20
MWSUG 2010 Ideas and Examples in Generalized Linear Mixed Models David A. Dickey 12
MWSUG 2010 PROC LIFEREG or PROC PHREG Dachao Liu 9
MWSUG 2010 PROC MIXED: Underlying Ideas with Examples David A. Dickey 19
MWSUG 2010 The Next Generation: SAS/STAT 9.22 Maura E. Stokes 20
MWSUG 2010 Using SAS to Assess and Model Time-to-Event Data with Non-Proportional Hazards Michael G. Wilson 24
SESUG 2010 A Macro for Calculating Summary Statistics on Left Censored Environmental Data using the Kaplan-Meier Method Dennis J. Beal source 6
SESUG 2010 The Next Generation: SAS/STAT 9.22 Maura E. Stokes,
Bob Rodriguez,
Robert A. Cohen		 source 20
PharmaSUG 2010 Linear Mixed Models in Clinical Trials using PROC MIXED Danyang Bing,
Xiaomin He		 12
SGF 2010 Analyzing Interval-Censored Survival Data with SAS Ying C. So,
Gordon Johnston		 source 14
SGF 2010 Ideas and Examples in Generalized Linear Mixed Models David A. Dickey source 12
SGF 2010 Improving Your Statistical Consulting Prowess by Adding R to Your SAS Repertoire Mark Austen,
Jeffrey M. Gossett,
Maria S. Melguizo,
Chan-Hee Jo		 source 11
SGF 2010 Not Hazardous to Your Health: Proportional Hazards Modeling for Survey Data with the SURVEYPHREG Procedure Pushpal K. Mukhopadhyay source 13
SGF 2010 SAS 9.2 Business Analytics Framework and IBM PowerVM Virtualization Deployment Scenarios Darrell Barton,
Frank Battaglia,
Alfredo Mendoza		 source 12
SGF 2010 Survival Analysis: Overview of Parametric, Nonparametric, and Semiparametric Approaches and New Developments Joseph C. Gardiner source 23
SGF 2010 The Next Generation: SAS/STAT 9.22 Maura E. Stokes,
Robert N. Rodriguez		 source 20
SESUG 2009 A Logistic Regression Model to Predict Freshmen Enrollments Vijayalakshmi Sampath,
Andrew Flagel		 source 12
SESUG 2009 Imputation for Censored Observations in Survival Studies Allowing for a Positive Cure Rate Alan B. Cantor source 6
SESUG 2009 PROC MIXED: Macro to assess fixed and random effects for significance using the Likelihood Ratio test and the approximate Mixture Method Barbara H. Bardenheier source 7
MWSUG 2009 Group Sequential Analysis Using the New SEQDESIGN and SEQTEST Procedures Yang Yuan 20
NESUG 2009 Using the New SURVEY Procedures From a Modeling Perspective Jonas V. Bilenas 13
WUSS 2009 A Biometric Analysis of Twin Data Using PROC MIXED Mo Zheng source 8
WUSS 2009 Guidelines for Reliability, Confirmatory and Exploratory Factor Analysis Diana D. Suhr,
Mary Shay		 source 15
WUSS 2009 Using PROC LOGISTIC to Estimate Willingness to Pay for Fresh Produce Mikael Peterson source 4
PharmaSUG 2009 Illustrative Logistic Regression Examples using PROC LOGISTIC: New Features in SAS/STAT 9.2 Robert G. Downer,
Patrick J. Richardson		 11
PharmaSUG 2009 The Existence of Maximum Likelihood Estimates for the Logistic Regression Model William F. McCarthy,
Nan Guo		 12
PharmaSUG 2009 Toolkits for Simulation Huei-Ling Chen 6
SGF 2009 Easier Exploratory Analysis for Epidemiology: A Grad Student "How-To" Paper Elisa L. Priest,
Brian Adams,
Lori A. Fischbach		 source 11
SGF 2009 Group Sequential Analysis Using the New SEQDESIGN and SEQTEST Procedures Yang Yuan source 20
NESUG 2008 SAS Program for Bivariate Growth Curve with Kalman Filter Amy E. Begley,
Qianyu Dang,
Patricia R. Houck,
Sati Mazumdar		 6
PharmaSUG 2008 Automated SAS Macro for Adverse Event Logistic Regression Analysis Suhas R. Sanjee 8
PharmaSUG 2008 Sample Size Estimation for Trials of Recurrent Events Kuolung Hu 8
PharmaSUG 2008 The Logic and Logistics of Logistic Regression Lawrence Rasouliyan,
Dave P. Miller		 14
PharmaSUG 2008 TPHREG and GLMSELECT: Using the CLASS statement in SAS 9.1 Laura E. Archer 11
SGF 2008 Convergence Failures in Logistic Regression Paul D. Allison source 11
SGF 2008 Data Mining Application of Non-Linear Mixed Modeling in Water Quality Analysis Anpalaki J. Ragavan source 14
SGF 2008 How to Use SAS to Fit Multiple Logistic Regression Models Anpalaki J. Ragavan source 13
SGF 2008 PROC MIXED: Underlying Ideas with Examples David A. Dickey source 18
SGF 2008 Reliability and Validity Testing using SAS/STAT Andrea Roofe source 8
NESUG 2007 Nonlinear Programming for Maximum Likelihood Estimation Robert J. Gallop 12
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 PROC MIXED: Underlying Ideas with Examples David A. Dickey source 19
SESUG 2007 Virtual and Traditional Teams: Are they Really Different? (Development and Validation of a Measure using SAS/STAT) Andrea J Roofe source 12
PNWSUG 2007 Utilizing PHREG for Cox proportional hazards regression modeling with time-varying covariates Marla J. Husnik,
Eugene Huang		 14
SGF 2007 Growing Up Fast: SAS 9.2 Enhancements to the GLIMMIX Procedure Oliver Schabenberger source 20
SGF 2007 Population Pharmacokinetics Studies with Nonlinear Mixed Effects Modeling Zaizai Shen,
David Lu		 source 11
SGF 2007 SAS Macros for Automated Model Selection When the Response Variable Is Nominal-Needs and Solutions Involving PROC CATMOD Bonnie E. Williams,
Todd Kegan		 source 12
PNWSUG 2006 You Can't Stop Statistics: SAS/STAT Software Keeps Rolling Along Maura E. Stokes,
Robert N. Rodriguez		 32
PHUSE EU 2006 Analysis of incomplete two-period crossover trials with SAS PROC MIXED Jochen Müller-Cohrs source 8
WUSS 2006 Get the Correct Hazard Ratio from SAS PROC PHREG Procedure Betty Ying Wang source 7
WUSS 2006 PROC GENMOD with GEE to Analyze Correlated Outcomes Data Using SAS Tyler C. Smith,
Besa Smith		 source 14
WUSS 2006 The Basics of Structural Equation Modeling Diana D. Suhr source 19
WUSS 2006 The Logic and Logistics of Logistic Regression Lawrence Rasouliyan,
Dave P. Miller		 source 14
NESUG 2006 Statistical analysis of clustered data using SAS Gui-Shuang Ying,
Chengcheng Liu		 13
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
SUGI 2006 Exploratory or Confirmatory Factor Analysis? Diana D. Suhr source 17
SUGI 2006 Fixed Effects Regression Methods in SAS Paul D. Allison source 20
SUGI 2006 MDIRT-FIT: SAS Macros for Fitting Multidimensional Item Response Sung-Hyuck Lee source 9
SUGI 2006 You Can't Stop Statistics Maura E. Stokes,
Robert N. Rodriguez		 source 32
WUSS 2005 A Comparison of Missing Data Handling Methods Catherine Truxillo source 20
WUSS 2005 Principal Component Analysis vs. Exploratory Factor Analysis Diana D. Suhr source 10
SUGI 2005 Benchmark Dose Estimation Using SAS Matthew W. Wheeler source 9
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 Parameterizing Models to Test the Hypotheses You Want: Coding Indicator Variables and Modified Continuous Variables David J. Pasta source 20
SUGI 2005 Principal Component Analysis versus Exploratory Factor Analysis Diana D. Suhr source 11
SUGI 2005 Single Event Timing Model with Heterogeneity: Predicting the Time of the First Home Purchase by Immigrants Eugene Brusilovskiy source 9
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 the Proportional Odds Model for Health-Related Outcomes: Why, When, and How with Various SAS Procedures Marc Gameroff source 8
WUSS 2004 Beyond Binary Outcomes: PROC LOGISTIC to Model Ordinal and Nominal Dependent Variables Eric P. Elkin source 8
WUSS 2004 Parameterizing Models to Test the Hypotheses You Want: Coding Indicator Variables and Modified Continuous Variables David J. Pasta source 12
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
MWSUG 2004 Presenting the Binary Logit Model Effectively using SAS Hun Myoung Park 11
PharmaSUG 2004 Making Model Selection in Linear Mixed-Effects Models An Easy Process: A SAS Macro Procedure Henry Cheng,
Yuli Xie,
Elizabeth Reinbolt		 4
SUGI 2004 Assessing Model Fit and Finding a Fit Model Margaret L. Bogle,
Rajiv Goel,
Robert M. Hamer,
Chan-Hee Jo,
Eric Siegel,
Pippa M. Simpson		 source 17
SUGI 2004 Bayesian Model Averaging Using SAS Software Melissa Whitney,
Ngo Long		 source 9
SUGI 2004 Creating Scales from Questionnaires: PROC VARCLUS vs. Factor Analysis David J. Pasta,
Diana D. Suhr		 source 19
SUGI 2004 Head of the CLASS: Impress Your Colleagues with a Superior Understanding of the CLASS Statement in PROC LOGISTIC Michelle L. Pritchard,
David J. Pasta		 source 9
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 Some Statistical Strategies for Analyzing Confirmatory Studies Involving One or More Occurrences of Primary Events Gary G. Koch,
Maura E. Stokes		 source 21
SESUG 2003 Methods of Dealing with Values Below the Limit of Detection using SAS Carry W. Croghan,
Peter P. Egeghy		 source 5
PharmaSUG 2003 Likelihood Approach in Estimation and Testing Problems Involving Grouped Data Daniel Bonzo,
InfoVision Consultants		 8
SUGI 2003 A SAS/IML Program for Mapping QTL in Line Crosses Chenwu Xu,
Shizhong Xu		 source 6
SUGI 2003 An Introduction to the Analysis of Mixed Models Dallas E. Johnson source 4
SUGI 2003 Estimation of Prevalence Ratios When PROC GENMOD Does Not Converge James A. Deddens,
Martin R. Petersen,
Xiudong Lei		 source 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
SESUG 2002 Analysis of Dosage-Response Data in Agricultural Research K. Bondari source 6
PharmaSUG 2002 Performing Logistic Regression on Survey Data with the New SURVEYLOGISTIC Procedure Anthony B. An 10
SUGI 2002 Performing Logistic Regression on Survey Data with the New SURVEYLOGISTIC Procedure Anthony B. An source 9
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
SESUG 2001 Ideas on Variable Selection and Alternative Links in Procedure CATMOD Kimberly Hughes DeJarnatt,
John Brown,
Siloam Springs		 source 4
SCSUG 2001 Ideas on Variable Selection and Alternative Links in Procedure CATMOD Kimberly DeJarnatt,
James E. Dunn		 4
SCSUG 2001 Using the SAS System to Study the Gender and Level Measurement Equivalence of a Multi-rater Survey Jim Penny 6
SUGI 2001 Approximations to Distributions of Test Statistics in Complex Mixed Linear Models Using SAS PROC MIXED G. Bruce Schaalje source 6
SESUG 2000 Performing Exact Logistic Regression with the SAS R /AD System Robert E. Derr source 10
WUSS 2000 Analyzing Multiple Health Outcomes Using the SAS System's PROC CATMOD Besa Smith source 5
WUSS 2000 SAS STAT applications in Econometrics Mathura Thillainathan,
George C. J. Fernandez		 source 10
SUGI 2000 Performing Exact Logistic Regression with the SAS System Bob Derr source 10
NESUG 1999 Input Selection, Performance Evaluation, and Credit Risk Analysis Shirley Tsai,
David Hamilton		 10
NESUG 1999 The missing link: PROC GENMOD Margaret Ann Goetz 3
MWSUG 1999 Longitudinal Data Analysis Repeated-Measure ANOVA and Mixed Models Nancy E. Briggs,
Ching-Fan Sheu		 6
SEUGI 1999 Using SAS/IML to fit embedded models to accelerated life test data Alan John Watkins,
Richard E. Johnson		 source 7
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 Simulation and Estimation of Fractionally Integrated Time Series Jeffrey S. Butler source 6
SUGI 1999 Using SAS Macros to Develop Confidence Intervals for the Weibull and Extreme Value Distributions Using Type II Censored Data Scott M. Jordan,
Muhammad Zaman		 source 6
WUSS 1998 Investigating the Performance of Model Selection Information Criteria Using SAS/IML and SAS/MACRO Long Ngo source 6
NESUG 1998 Risk Evaluation after Heart Valve Replacement by PROC PHREG Choa Chen 7
SESUG 1998 Modern Psychometric Theory: Using SAS to Calculate IRT Ability Estimates Jeffrey D. Kromrey,
Cynthia G. Parshall,
Walter M. Chason,
Qing Yi		 5
SEUGI 1998 A SAS/IML algorithm for maximum likelihood estimation in the Three Parameter Burr XII Distribution Alan John Watkins source 7
SUGI 1998 Statistical Process Monitoring of Correlated Binary and Count Data Using Mixture Distributions Jose G. Ramirez,
Brenda S. Cantell,
Randall S. Collica		 source 7
SCSUG 1997 Reliability Data Analysis in the SAS System Gordon Johnston 10
SCSUG 1997 The Use of PROC ARIMA to Test An Intervention Effect Neil S. Fleming,
Eric Gibson,
David G. Fleming		 8
PNWSUG 1997 Qualitative Choice Models Donald M. Perry 2
WUSS 1997 Reliability Data Analysis in the SAS System Donna O. Fulenwider,
Gordon Johnson		 source 10
NESUG 1997 Estimation of Sample Selection Models with SAS/IML Software Charles B. Hallahan 9
NESUG 1997 Nonlinear Mixed Effects Models, a tool for analyzing repeated-measurements data whose function is nonlinear in the parameters. Suzette Blanchard 7
NESUG 1997 Using Logistic Regression to Test for Interaction in the Presence of Zero Cells Lisa Suchower 10
MWSUG 1997 Reliability Data Analysis in the SAS System Gordon Johnston 10
SESUG 1997 Analysis of Repeated Measures and Longitudinal Data Jane Pendergast 8
SEUGI 1997 Investigating likelihoods for lifetime distribution using SAS software Alan John Watkins source 6
SEUGI 1997 Modelling of road deterioration including lifetime distribution and the Cox model Emmanuel Courilleau source 11
SEUGI 1997 Weighted Poisson Analysis à la Goodman using SAS software Rian Vogelesang source 14
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 The Tobit Model: An Example of Maximum Likelihood Estimation with SAS/IML Charles B. Hallahan source 6
SESUG 1996 Generalized Linear Models (Logistic Regression), a Comparison of Available Options and Output from the Catmod, Probit, Logistic, and Genmod Procedures Margaret A. Connolly 6
SESUG 1996 Quasicomplete Separation in Logistic Regression: A Medical Example Madeline J. Boyle 6
NESUG 1996 Maximum Likelihood Estimation with SAS/IML Charles B. Hallahan 7
MWSUG 1996 Detecting Changes in Mean of Correlated Data Tze-San Lee,
Lei Zhang		 4
WUSS 1996 Logistic Regression: From SAS Coding to Statistical Interpretation Elizabeth Li source 9
PNWSUG 1996 Net Impact for Program Evaluation Modeling and SAS Programming Boqing Wang 18
SEUGI 1996 Using the SAS system to fit the BURR XII distribution to lifetime data Alan John Watkins source 8
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 A SAS Program for the Assessment of Unbalanced Data in Two- Sequence, Three-Period CrossoverTrials Annpey Pong,
Shein-Chung Chow		 source 6
SUGI 1996 Analysis of Unbalanced Mixed Model Data Ramon C. Littell source 6
SUGI 1996 Imputation of Data Missing Due to Truncation --- A SAS Macro for Maximum Likelihood Estimates Using Symmetry Property Zhengyu Wang,
ViswanaThan Ramakrishnan,
John M. Davis		 source 6
SUGI 1996 Repeated Measures Analysis with Discrete Data Using the SAS System Gordon Johnston source 5
SUGI 1996 Teaching the SAS System as an Academic Subject Andrew H. Karp source
SUGI 1996 Using PROC ARIMA to Test an Intervention Effect Neil S. Fleming,
Eric Gibson,
David G. Fleming		 source 10
NESUG 1995 A Survey of Capability Invoices Dennis W. King 11
NESUG 1995 Estimation of Nonlinear Models: A Computational Review D. Das Purkayastha 8
NESUG 1995 More on PROC PHREG: Conditional Logistic Regression (or Should We Do Another Study..?) Peter P. Gaccione 10
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
SEUGI 1995 Regional Econometric Modeling An Application of SAS/IML Software Jorgen Lauridsen source 20
SEUGI 1995 Using the SAS System in the Development of Frameworks for the Analysis of Accelerated Life Testing Experiments Alan John Watkins source 10
SUGI 1995 A Primer on Poisson Regression using SAS/STAT Software Methods and Interpretation of Results Richard McNally source 4
SUGI 1995 Bartlett Correction of Binomial Regression Analyses of Small Samples Lawrence Moulton,
Roy St. Laurent,
Lisa Weissfeld		 source 5
SUGI 1995 Calculating Confidence Intervals on Proportions of Variability Using the VARCOMP and IML Procedures Annette M. Green,
David Umbach		 source 6
SUGI 1995 Maximum Likelihood Estimation with PROC NLP and SAS IML Software Wolfgang Hartmann,
James J. Ashton		 source 7
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 Accelerating Maximum Likelihood Classification: An IML Application Cecil R. Hallum,
D. Mark Carpenter		 source 4
SUGI 1994 Computing Case Diagnostics for Structural Equation Models Noel G. Cadigan source 5
SUGI 1994 Estimating Spatial Regression Models with SAS/IML Charles B. Hallahan source 5
SUGI 1994 Interval-Censored Survival Data Ying C. So source 7
SUGI 1994 Neural Networks and Statistical Models Warren S. Sarle source 13
SUGI 1994 Nonlinear Regression Analysis and Nonlinear Simulation Models Donald Erdman,
Mark Little		 source 9
SEUGI 1993 Generalised Linear Model and Correspondence Analysis. Application to the Goitre Problem in Mali Michel Tenehaus source 28
SEUGI 1993 The Analysis of Repeated Measures Designs Using the SAS System Alun Bedding source 9
SUGI 1993 A Tutorial on Logistic Regression Ying C. So source 6
SUGI 1993 Application of Conditional Logistic Regression Methods to Event History and Multiple-Choice Data Dan Steinberg source 4
SUGI 1993 Likelihood Ratio Tests for Regression Coefficients from the Cox Proportional Hazards Model Using the PHREG Procedure Laurent M. Kassalow source 6
SUGI 1993 SAS Software to Fit the Generalized Linear Model Gordon Johnston source 8
SUGI 1993 The Pricing of Stock Returns That Have a Time Varying Beta Coefficient Using the SAS/IML Module Michael Murray source 7
SCSUG 1992 Calculating the Odds Ratio and Goodness of Fit Statistics for Logistic Regression Models Using PROC LOGISTIC Chuan-Chuan C. Wun 19
SCSUG 1992 The Use of PROC ARIMA to Perform Time-Series Intervention Analysis of the Impact of the Texas 1989 Motorcycle Helmet Law on Total and Head-Related Fatalities Neil S. Fleming 21
NESUG 1992 An In-Depth Look at the PHREG Procedures Peter P. Gaccione 9
SUGI 1992 A Bootstrap Evaluation of the EM Algorithm for Censored Survival Data George W. Pasdirtz source 6
SUGI 1992 Extending the SAS System's Statistical Capabilities with SAS/IML Software Charles B. Hallahan source 10
SUGI 1992 Using the CATMOD Procedure to Estimate Linkage between Pairs of Gene Loci from Offspring of Selfed Heterozygotes Kent M. Eskridge,
William Compton,
Lomas Tulsieram		 source 6
SEUGI 1991 An Example of the Use of Historical Information in the Analysis of Pharmaceutical Screening Trials Egbert Biesheuvel,
R. A. J. Wixley		 source 9
SEUGI 1991 Attributable Risk Estimation Using SAS/STAT Software Olaf Gefellar source 8
SEUGI 1991 Future Directions of Statistical Software with the SAS System David M. DeLong source 20
SUGI 1991 A Macro For Principal Component Logistic Regression Brian D. Marx source 6
SUGI 1991 Analysis of Sparse Repeated Categorical Measurement Data Alan Agresti,
Stuart Lipsitz,
Joseph B. Lang		 source 9
SEUGI 1990 Prediciting and Understanding Steam Generator Tubes Lifetime Using SAS Software Survival Procedures P. Pittner,
T. Riffard		 source 8
SUGI 1990 A SAS Macro for the Box-Cox Transformation: Estimation and Testing Charles B. Hallahan source 6
SUGI 1990 Analysis of Covariance: Repeated Measures and Split-Plot Designs Gilda P. Pareja source 5
SUGI 1989 Most Creative Use of the Software-Monochrome Leslie Worf source 116
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 Using the SAS System for Empirical Bayes Estimation and Mapping of Suicide Rates in California Joseph L. Annest,
Marilyn Kirk,
Kung-Jong Lui,
Beverly Martinez		 source 4
SUGI 1989 Weighted Multicollinearity Diagnostics for Logistic Regression Brian D. Marx,
Eric P. Smith		 source 6
SUGI 1988 Detection of Influential Observations in Logistic Regression Using the SAS System Charles S. Davis source 6
SUGI 1988 Using SAS Software for Estimating the Probability of Being in Response Brenda W Gillespie,
Charles B. Scott		 source 5
SUGI 1987 Interpretation and Diagnostics of the Multinomial Logistic Regression Dan Steinberg source 6
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 Treatment of Lagged Dependent Regressors and Autocorrelated Errors in SAS/ETS Software Thomas B. Fomby,
Joseph G. Hirschberg		 source 6
SUGI 1987 Variance Component Estimation with the SAS System Ramon C. Littell,
Barbara G. McCutchan		 source 6
SUGI 1986 Inference from the Incomplete Longitudinal Design: A Collection of SAS Macros James Rochon source 6
SUGI 1986 Maximum Likelihood Estimation for a Mixture of Larval Instars Richard L. Berg source 5
SUGI 1986 Programs for the GMANOVA and Extended GMANOVA Models Vernon M. Chinchilli,
Ronald K. Elswick		 source 8
SUGI 1986 Repeated Application of a Generalized Logistic Model To Count Data Using PROC MATRIX Linda Williams Pickle source 6
SEUGI 1985 New Features of the SAS/ETS and SAS/OR Software in Version 5 John C. Brocklebank source 37
SUGI 1985 A SAS Macro for Logistic Discrimination for Three or More Populations James E. Dunn,
Eileen C. King		 source 6
SUGI 1985 Application of the SAS System to Regression Analysis of Tumor Prevalence Data Saeid B. Amini,
Debra L. Palka		 source 7
SUGI 1985 Changes and Enhancements to SAS/ETSSoftware David M. DeLong,
Leigh A. Ihnen,
Mark Little		 source 12
SUGI 1985 MACRO LGTREG for Logistic Regression and Associated Diagnostics Thomas F. Devlin,
Barbara J. Weeks		 source 6
SUGI 1985 Taking MDS Beyond Similarity Data J.O. Ramsay source 7
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 An M-Population Covariance Stabilization: PROC VARSTB James E. Dunn,
Mike Zodrow		 source 6
SUGI 1984 Changes and Enhancements to SAS/ETS Procedures David M. DeLong,
Leigh A. Ihnen,
Mark Little		 source 6
SUGI 1984 Computing for Unbalanced Repeated Measures Experiments Kenneth N. Berk source 7
SUGI 1984 The Use of CATMOD for Repeated Measurement Analysis of Categorical Data Gary G. Koch,
William M. Stanish		 source 10
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 An Algorithm for Producing Exact Maximum Likelihood Estimates for an ARIMA(p,q) Process Carol M. Reilly source 3
SUGI 1983 On Estimating Spline Regressions Lawrence C. Marsh source
SUGI 1983 Overview of Categorical Data Analysis Methods Ingrid A. Amara,
Susan Atkinson,
Gary G. Koch,
William M. Stanish		 source 10
SUGI 1983 PROC DISCRETE-A Procedure for Fitting Discrete Probability Distributions Charles E. Gates,
James P. Geaghan,
George D. Williams		 source 4
SUGI 1983 The Use of Rank Analysis of Covariance in Analyzing Censored Survival Data Saeid B. Amini,
Peter A. Lachenbruch,
Robert F. Woolson		 source 7
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 Approaches to Estimating Covariance Matrices with Partial Multinomial Data Mark W. Riggs,
W.B. Smith		 source 10
SUGI 1982 Influential Cases and Transformations R. Dennis Cook,
Sanford Weisberg		 source 6
SUGI 1982 Multidimensional Scaling by Least Squares Cynthia H. Null,
Warren S. Sarle		 source 8
SUGI 1982 Paired Comparison Estimation and Analysis: A SAS Macro Ramon C. Littell,
Walter W. Offen		 source 5
SUGI 1982 PROC TETCORR: Correlations between Categorical and Continuous Variables. J. Philip Miller,
Michael A. Province,
Reimut Wette		 source 4
SUGI 1982 Weibull Regression and Hazard Estimation Jan M. Hanley,
William H. Rogers		 source 11
SUGI 1980 An Overview of Survival Analysis and SAS Irving K. Hwang source
SUGI 1980 Recent Developments in BMDP of Special Interest to SAS Users James W. Frane source 8
SUGI 1979 Application of Stepwise MANOVA and MANCOV Using SAS Chandu M. Patel source 9
SUGI 1978 Maximum Likelihood Estimation of the Multivariate Logistic Martha McCrate,
Michael A. Province,
Reimut Wette		 source 3
SUGI 1978 Use of SAS Procedures in Estimating Survival Curves Ernest Hilderbrand,
Melvin Moeschberger		 source 7
SUGI.ONE 1976 Econometric Uses of SAS Max Moszer,
Martha S. Shuler		 source 26

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