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406 papers and 8 presentations; 371 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 2026 Beyond Imitation: Selecting Synthetic Data with Purpose and Precision Sundaresh Sankaran,
Pritesh Desai,
Sherrine Eid		 source 9
PharmaSUG 2026 The (ODS) Output of Your Desires: Creating Designer Reports and Data Sets Louise S. Hadden source 12
PHUSE US 2026 Demystifying TMLE: A Practical Approach for Clinical Data Scientists Joshua Enxing source
presentation source		 12
PHUSE US 2026 Enhancing ISS Analyses with the Continuity-Corrected CMH Method: An SAS-Based Solution for Zero-Event Strata Ji Qi,
Kaixiang Li		 source
presentation source		 5
PHUSE APAC 2026 From Data to Digital Phenotypes: Modelling High-Dimensional PROs and Actigraphy Data in Decentralized Psychiatric Trials Sakshi Kaushik source
presentation source		 14
PHUSE EU 2025 Evaluating the Use of Real-World Data (RWD) as a Synthetic Control Group: A Statistical Approach Vasiliki Economou,
Dimitrios Kounelis		 source
poster source		 17
MWSUG 2025 The (ODS) Output of Your Desires: Creating Designer Reports and Data Sets Louise S. Hadden source 12
SESUG 2025 The (ODS) Output of Your Desires: Creating Designer Reports and Data Sets Louise S. Hadden 12
WUSS 2025 The (ODS) Output of Your Desires: Creating Designer Reports and Data Sets Louise S. Hadden source 12
PharmaSUG 2025 Association of Alzheimer-s Disease with Cardiovascular Disease and Depression in Older Adults: Findings from the 2018 Nationwide Inpatient Sample Prayag Shah source 27
PharmaSUG 2025 How to compute common clinical trials statistics in R Oleksandr Babych source 15
PharmaSUG 2025 The (ODS) Output of Your Desires: Creating Designer Reports and Data Sets Louise S. Hadden source 12
MWSUG 2024 Building a SAS Data Viz Toolkit [presentation] Sara Richter source 78
PHUSE EU 2024 Revolutionising Literature Reviews with a GPT-Assisted Tool: Enhanced Search, Extraction and Visualisation Yingjia Chen,
Martin Schaerer		 source
presentation source		 12
SESUG 2024 A Comprehensive Analysis of the Relationship Between Depression, Sleep Deprivation, and Self-Esteem Using Advanced Statistical Methods Muslihat Adejoke Gaffari source 43
WUSS 2024 Regression Analysis Made Easy Using SAS Studio Zheyuan (Walter) Yu source 42
WUSS 2023 D-I-D the policy have an impact? Difference-in-difference methods applied to survey data in SAS Melanie Dove source 7
WUSS 2023 Leveraging Logistic Regression and Bootstrap Sampling to Assess a Decision Threshold in Classification Predictive Analytics Colleen E. McGahan source 15
WUSS 2023 Regression Analysis Made Easy Using SAS Studio Kirk Paul Lafler,
Zheyuan (Walter) Yu,
Nuoer Lu,
Nicklas (Rebel) Yee,
Yanzhang Gavin Chen,
Kai Kang		 source 43
WUSS 2023 Survey Data Analysis in SAS Denis Nyongesa,
Marianne Jurasic,
Gregg Gilbert,
Tamara Lischka		 source 11
SESUG 2023 Designing Against Bias: Identifying and Mitigating Bias in Machine Learning and AI David J. Corliss source 9
SESUG 2023 Regression Analysis Made Easy Using SAS Studio Kirk Paul Lafler,
Zheyuan (Walter) Yu,
Nuoer Lu,
Daniel Qian,
Kai Kang,
Yanzhang Gavin Chen,
Nicklas (Rebel) Yee,
Yixuan (Jason) Xiang		 source 43
PharmaSUG 2023 Guidelines for the Statistical Analysis in German Dossier Submissions Meiling Gao,
Xi Qian,
Hui Mao		 source 8
SAS Explore 2022 Aircraft Landing Problem: An Optimization Solution [video] Jay Laramore source
youtube
PharmaSUG 2022 Getting odds ratio at Preferred Term (PT) level for safety analysis in R Kamleshkumar Patel,
Jigar Patel		 source 4
PHUSE US 2022 Volcano Plot for Adverse Event Analysis in R [presentation] Kamleshkumar Patel source
video		 15
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 Exploring Categorical Data Using Unsupervised Graph-based Machine Learning [presentation] Irina Kotenko,
Kostiantyn Drach		 source
video		 34
PHUSE US 2021 Table-based Data Visualizations Using R [presentation] Matthew Kumar source
video		 26
PharmaSUG 2021 Data Visualization in Real World Data (RWD) and Health Economics Outcomes Research (HEOR) using (Statistical Analysis Software) SAS Swapna Ambati source 45
SGF 2021 Disproportional Impact of COVID-19 on Marginalized Communities David J. Corliss source
presentation		 10
SGF 2021 Pandemic Pandemonium Hannah Flynt,
Maryam Taherirani,
Sean Everett,
Trinh Phan		 source 7
SGF 2020 Fitting Statistical Models with PROC MCMC Mark Ghamsary source 26
SGF 2020 From Santiago to the Spirit Lake Nation: 30 Things I Learned in 30 Years as a Statistical Consultant AnnMaria De Mars source 20
SGF 2020 Multinomial vs. Ordinal. Does model selection make a difference? for SAS Global Forum 2020 Corey Leadbeater source 15
SGF 2020 Propensity Score Matching with Survey Data Bocheng Jing source 14
SGF 2020 Testing Hypotheses for Equivalence and Non-inferiority with Binary and Survival Outcomes Joseph C. Gardiner source 23
SGF 2020 The New solveBlackbox Action in SAS Optimization 8.5 Edward P. Hughes source 14
SGF 2020 Use SAS to Model Non-Linearity Xiaoting Wu,
Donald S. Likosky		 source 12
PharmaSUG 2020 %MVMODELS: a Macro for Survival and Logistic Analysis Jeffrey P. Meyers source 23
PharmaSUG 2020 Calculation of Cochran-Mantel-Haenszel Statistics for Objective Response and Clinical Benefit Rates and the Effects of Stratification Factors Girish Kankipati,
Chia-Ling (Ally) Wu		 source 8
PharmaSUG 2020 Demographic Table and Subgroup Summary Macro %TABLEN Jeffrey P. Meyers source 12
SESUG 2019 Don't Let Complex Survey Data Get the Best of You! SAS Survey PROCs for Categorical Data Analysis Charlotte Baker source 14
SESUG 2019 Glass Box Neural Networks Ross Bettinger source 14
SESUG 2019 The Thorn in My Side!! Logistic Regression Continuous Variables that Violate the Assumption of Linearity on the Log-odds (Logit) Scale: How to Identify and What to Do? Janet M. Grubber,
Cynthia J. Coffman		 source 13
WUSS 2019 Ordinal vs. Multinomial: Does Model Selection Make a Difference? Corey Leadbeater source 14
PharmaSUG 2019 Patterns of risk factors and drug treatments among Hypertension patients Youngjin Park source 14
SGF 2019 Airbnb New York City: Demystifying the Superhost Program Soumya Ranjan Kar Choudhury source 7
SGF 2019 Data-Driven Agent Allocation in a Process using Machine Learning and Optimization in SAS Lokendra Kumar Devangan source 9
SGF 2019 Don't Let Complex Survey Data Get the Best of You! SAS Survey PROCs for Categorical Data Analysis Charlotte Baker source 16
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 Railways Scheduling and Rolling Stock Optimization using SAS Ayush Tiwari,
Lokendra Devangan,
Malleswara Sastry Kanduri,
Faiz Hamid		 source 10
SGF 2019 The Benefits of Keeping It Casual: Investigating Stress-Mediated Health Outcomes with PROC CAUSALMED Daniel Muzyka,
Matthew Lypka		 source 19
SGF 2019 Thirteen Statistics Every Biostatistician Should Know AnnMaria De Mars source 20
SCSUG 2018 Are you in danger of stroke? An insight into the leading causes. Anjali Bansal source 17
MWSUG 2018 Using your FREQ effectively: Displays to Decipher Proportional Odds in Ordinal Regression Robert G. Downer 11
WUSS 2018 An Efficient Way to Output Univariate Analysis Results with Multiple Predictors Bocheng Jing,
Kathy Fung,
W. John Boscardin		 source 7
WUSS 2018 Optimizing Exam Schedules at Oklahoma State University Thu Nguyen source 12
PHUSE US 2018 Programmers are from Mars and Statisticians are from Venus Shweta Padmanaban,
Sangeetha Sathaiah		 source
presentation source		 6
PharmaSUG 2018 A One-Sided Fisher's Exact Test: A Tail of Clinical Worsening William Coar source 8
PharmaSUG 2018 Visually Exploring Odds Ratios between Risk Factors for Fetal and Infant Mortality in Kent County, MI Ruth Kurtycz source 11
SGF 2018 A One-Sided Fisher's Exact Test: A Tail of Clinical Worsening Bill Coar source 9
SGF 2018 Getting to Know the No-Show: Predictive Modeling of Missing a Medical Appointment Joe Lorenz source 10
SGF 2018 Insights into Using the GLIMMIX Procedure to Model Categorical Outcomes with Random Effects Kathleen Kiernan source 23
SGF 2018 Optimization Modeling with Python and SAS Viya Sertalp Cay,
Jared Erickson		 source 11
SGF 2018 Optimizing Inventory of Slow-Moving Products Using SAS Optimization Malleswara Sastry Kanduri,
Amy Mcarthur		 source 8
SGF 2018 Penalized Variable Selection and Quantile Regression in SAS : An Overview Russell M. Lavery source 28
SGF 2018 Using SAS/OR to Optimize Scheduling and Routing of Service Vehicles Robert C. Pratt source 27
SESUG 2017 Backward Variable Selection for Logistic Regression Based on Percentage Change in Odds Ratio Evan Kwiatkowski source 6
SESUG 2017 Finding the Gold in Your Data: An Overview of Data Mining David A. Dickey source 25
SESUG 2017 Meta-Analysis and Matrix Multiplication: Adapting an IML-Based Macro for DerSimonian and Laird's Error Calculation to use Base SAS Venita DePuy source 16
PHUSE EU 2017 Visualizing Multiple Endpoints: Extending the Use of Forest Plots in Clinical Trials James R. Johnson,
Mark Jaros		 source
presentation source		 10
MWSUG 2017 Exploring the Relationship Between Substance Abuse and Dependence Disorders and Discharge Status: Results and Implications Deanna Naomi Schreiber-Gregory 25
WUSS 2017 Next Best Offer Analytics using SAS Robin E. Way,
William Eisenhauer		 source 12
PharmaSUG 2017 Multinomial Logistic Regression Models With Sas Proc Surveylogistic Marina Komaroff source 7
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 Moment-Matching Approach for Generating Synthetic Data in SAS Brittany Bogle,
Jared Erickson		 source 17
SGF 2017 An Investigation into Big Data Analytics Applied to Insurance Rebecca Peters,
Penny Holborn		 source 18
SGF 2017 Analyzing the Effectiveness of COPD Drugs Through Statistical Tests and Sentiment Analysis Indra Kiran Chowdavarapu,
Dursun Delen,
Vivek Manikandan Damodaran		 source 23
SGF 2017 Construction of a Disease Network and a Prediction Model for Dementia Jinwoo Cho source 14
SGF 2017 Dataninjas: Modeling Life Insurance Risk David Allen,
Seung Lee		 source 7
SGF 2017 Key Components and Finished Products Inventory Optimization for a Multi-Echelon Assembly System Sherry Xu,
Kansun Xia,
Ruonan Qiu		 source 7
SGF 2017 Optimize My Stock Portfolio! A Case Study with Three Different Estimates of Risk Aric LaBarr source 11
SGF 2017 Optimizing Delivery Routes with SAS Software Ben Murphy,
Bruce Bedford		 source 13
SGF 2017 Price Recommendation Engine for Airbnb Praneth Guggilla,
Singdha Gutha,
Goutam Chakraborty		 source 10
SGF 2017 Tables and Graphics That Will FREQ You Out Kathryn McLawhorn source 21
SGF 2017 The Three Amigos Factors: Determining Term Deposit Purchases: How a Bank Can Get Other People's Money Gina Colaianni,
Bogdan Gadidov,
Matthew Mitchell		 source 59
SGF 2017 The Truth Is Out There: Leveraging Census Data Using PROC SURVEYLOGISTIC Richard Dirmyer source 5
SGF 2017 Using a Population Average Model to Investigate the Success of a Customer Retention Strategy Colleen E. McGahan source 19
SGF 2017 Using SAS/OR Software to Optimize the Capacity Expansion Plan of a Robust Oil Products Distribution Network Shahrzad Azizzadeh source 9
SGF 2017 Using the LOGISTIC or SURVEYLOGISTIC Procedure and Weighting of Public-Use Data in the Classroom Tyler C. Smith,
Besa Smith		 source 9
SESUG 2016 Factors of Multiple Fatalities in Car Crashes Bill Bentley,
Gina Colaianni,
Kennedy Onzere,
Cheryl Joneckis,
Xuelei (Sherry) Ni		 source 62
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 Hierarchical Generalized Linear Models for Behavioral Health Risk-Standardized 30-Day and 90-Day Readmission Rates Allen Hom source
pptx		 20
WUSS 2016 How to analyze correlated and longitudinal data? Niloofar Ramezani source 8
PharmaSUG 2016 Unequalslopes: Making life easier when the proportional odds assumption fails Matthew J. Wiedel source 11
SGF 2016 An Application of the DEA Optimization Methodology to Optimize the Collection Direction Capacity of a Bank Miguel Díaz,
Oscar Javier Cortés Arrigui		 source
zip		 12
SGF 2016 Analyzing Non-Normal Binomial and Categorical Response Variables under Varying Data Conditions Niloofar Ramezani source 16
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 Factors of Multiple Fatalities in Car Crashes Bill Bentley,
Gina Colaianni,
Cheryl Joneckis,
Sherry Ni,
Kennedy Onzere		 source 60
SGF 2016 Latent Class Analysis Using the LCA Procedure Patricia A. Berglund source 18
SGF 2016 Portfolio Optimization with Discontinuous Constraint Taras Zlupko,
Robert Spatz		 source
zip
presentation		 11
SGF 2016 The Baker's Dozen: What Every Biostatistician Needs to Know AnnMaria De Mars source 17
SGF 2016 The Scheduler: Give Your Punch Data a New Dimension Ariel Kumpinsky source 7
SGF 2016 Using SAS Simulation Studio to Test and Validate SAS/OR Optimization Models Edward P. Hughes,
Emily Lada,
Leo Lopes,
Imre Polik		 source
zip		 10
SGF 2016 Using the OPTMODEL Procedure in SAS/OR to Find the k Best Solutions Robert C. Pratt source
zip		 17
MWSUG 2015 A Simple Adjustment for Selection Bias Through Use of Propensity Scoring Deanna Naomi Schreiber-Gregory 24
MWSUG 2015 Transitions in Depressive Symptoms After 10 Years of Follow-up Using PROC LTA in SAS and Mplus Seungyoung Hwang 11
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
WUSS 2015 Chi-Square and T-Tests Using SAS: Performance and Interpretation Jennifer L. Waller,
Maribeth H. Johnson		 source 12
WUSS 2015 Introduction to SAS Quantile Regression (PROC QuantSelect and PROC QuantReg ) Peter L. Flom source 25
WUSS 2015 Yes, PROC FREQ does that! AnnMaria De Mars source 15
PharmaSUG 2015 Transitions in Depressive Symptoms After 10 Years of Follow-up Using PROC LTA Seungyoung Hwang source 7
SGF 2015 Addressing AML Regulatory Pressures by Creating Customer Risk Rating Models with Ordinal Logistic Regression Edwin Rivera,
Jim West		 source 12
SGF 2015 Chi-Square and T-Tests Using SAS: Performance and Interpretation Jennifer L. Waller,
Maribeth H. Johnson		 source 12
SGF 2015 Forest Plotting Analysis Macro %FORESTPLOT Jeffrey P. Meyers,
Qian Shi		 source 18
SGF 2015 Getting Your Hands on Reproducible Graphs Rebecca Ottesen,
Leanne Goldstein		 source 19
SGF 2015 Lost in the Forest Plot? Follow the Graph Template Language AXISTABLE Road! Prashant Hebbar source
zip		 11
SGF 2015 Multilevel Models for Categorical Data Using SAS PROC GLIMMIX: The Basics Mihaela Ene,
Bethany A. Bell,
Genine L. Blue,
Elizabeth Leighton		 source 12
SGF 2015 Multiple Ways to Detect Differential Item Functioning in SAS Yan Zhang source 9
SGF 2015 Portfolio Construction with OPTMODEL Taras Zlupko,
Robert Spatz		 source 7
SGF 2015 Statistical Analysis of Publicly Released Survey Data with SAS/STAT Software SURVEY Procedures Donna Brogan source 20
SGF 2015 Using the OPTMODEL Procedure in SAS/OR to Solve Complex Problems Robert C. Pratt source
zip		 14
SESUG 2014 Don't be binary! Tales of Non-binary Categorical Regression Charlotte Baker source 6
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 To foam or not to foam: A survival analysis of the foam head that forms when a soda is poured Kate Phillips source 16
PharmaSUG CN 2014 Calculation of Confidence Intervals for Odds Ratio and Binomial Ratio Using StatXact PROCs Halimu Haridona 7
PharmaSUG CN 2014 Plotting Against Cancer: Creating Oncology Plots Using SAS Debpriya Sarkar 30
WUSS 2014 Getting Your Hands on Reproducible Graphics Rebecca Ottesen,
Leanne Goldstein		 source 17
WUSS 2014 Using PROC FACTOR for variable inclusion in PROC SURVEYLOGISTIC: A Case Study Deanna Naomi Schreiber-Gregory source 35
WUSS 2014 Using SAS and the Centers for Disease Control and Prevention 2010 Natality Data to Estimate the Effect Size of Prenatal Visits on Preterm Birth Melissa Borelli source 10
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 The Association of Morbid Obesity with Mortality and Coronary Revascularization among Patients with Acute Myocardial Infarction Ashwini S Erande,
Shaista Malik		 source 11
PharmaSUG 2014 The path less trodden - PROC FREQ for ODDS RATIO Manjusha Gondil,
Linga Reddy Baddam		 source 4
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 Automatic and Efficient Post-Campaign Analyses By Using SAS Macro Programs Justin Jia,
Amanda Lin		 source 12
SGF 2014 Building Gamer Segmentation in the Credit Card Industry Using SAS Enterprise Guide Yang Ge source 10
SGF 2014 Examples of Logistic Modeling with the SURVEYLOGISTIC Procedure Rob Agnelli source 17
SGF 2014 Healthcare Services Data Distribution, Transformation, and Model Fitting Dawit Mulugeta,
Jason Greenfield,
Tison Bolen,
Lisa Conley		 source 22
SGF 2014 How to Interpret SVD Units in Predictive Models? Murali Krishna Pagolu,
Goutam Chakraborty		 source 10
SGF 2014 Leveraging Publicly Available Data in the Classroom Using SAS PROC SURVEYLOGISTIC Tyler C. Smith,
Besa Smith		 source 18
SGF 2014 Medical Scoring for Breast Cancer Recurrence Nurul Husna Jamian,
Yap Bee Wah,
Nor Aina Emran		 source 13
SGF 2014 New Features in SAS/OR 13.1 Edward P. Hughes,
Robert C. Pratt		 source 15
SGF 2014 Plotting Against Cancer: Creating Oncology Plots Using SAS Debpriya Sarkar source 30
SGF 2014 The Traveling Baseball Fan Problem and the OPTMODEL Procedure Tonya Chapman,
Matthew V. Galati,
Robert C. Pratt		 source 27
SGF 2014 Using SAS to Evaluate Patient-Directed Quality of Care Interventions Scott P. Leslie source 10
WUSS 2013 A Tutorial on PROC LOGISTIC Arthur X. Li source 19
WUSS 2013 Proper Estimation of Relative Risk Using PROC GENMOD in Population Studies Kechen Zhao source 14
WUSS 2013 The Association of Morbid Obesity with Mortality and Coronary Revascularization among Patients with Acute Myocardial Infarction using ARRAYS, PROC FREQ and PROC LOGISTIC" Ashwini Erande,
Shaista Malik		 source 11
SESUG 2013 Chi-Square and T-Tests Using SAS: Performance and Interpretation Jennifer L. Waller,
Maribeth H. Johnson		 source 12
SESUG 2013 Finding the Gold in Your Data: An Overview of Data Mining David A. Dickey source 16
SESUG 2013 SAS Macros to Conduct Common Biostatistical Analyses and Generate Reports Dana Nickleach,
Yuan Liu,
Adam Shrewsberry,
Kenneth Ogan,
Sungjin Kim		 source 8
PHUSE EU 2013 Bayesian Statistics: Concept and Bayesian Capabilities in SAS Mark Janssens source
presentation source		 15
PHUSE EU 2013 Using PROC GENMOD to Analyses Ratio to Placebo in Change of Dactylitis Imgard Hollweck source
presentation source		 9
MWSUG 2013 A Tutorial on PROC LOGISTIC Arthur X. Li 19
MWSUG 2013 An Analysis of Risk Behavior Trends and Mental Health in American Youth Using PROC SURVEYLOGISTIC Deanna Naomi Schreiber-Gregory 15
MWSUG 2013 Analyzing Categorical Variables from Complex Survey Data Using PROC SURVEYFREQ Taylor Lewis 20
MWSUG 2013 Finding the Gold in Your Data: An Overview of Data Mining David A. Dickey 16
NESUG 2013 Exploring the Relationship Between Mental Health and Risky Behaviors in American Youth Using PROC SURVEYFREQ and SURVEYLOGISTIC Deanna Naomi Schreiber-Gregory 9
PharmaSUG 2013 Combining Analysis Results from Multiply Imputed Categorical Data Bohdana Ratitch,
Ilya Lipkovich,
Michael O'Kelly		 source 19
SGF 2013 Analyzing Partially Confounded Factorial Conjoint Choice Experiments Using SAS/IML Chin Khian Yong,
Song Lin Ng		 source
pdf		 11
SGF 2013 Assessing Drug Safety with Bayesian Hierarchical Modeling Using PROC MCMC and JMP Richard C. Zink source 13
SGF 2013 Chi-Square and T-Tests Using SAS: Performance and Interpretation Jennifer L. Waller,
Maribeth H. Johnson		 source 12
SGF 2013 DICHOTOMIZED_D: A SAS Macro for Computing Effect Sizes for Artificially Dichotomized Variables Aarti P. Bellara,
Harold Holmes,
Isaac Y. Li,
Jeanine L. Romano,
Jeffrey D. Kromrey,
Patrice Rasmussen,
Patricia Rodríguez de Gil,
Yi-Hsin Chen		 source 12
SGF 2013 Exploring Health Trends and Risk Behavior Analysis in American Youth Using PROC SURVEYFREQ and PROC SURVEYLOGISTIC Deanna Naomi Schreiber-Gregory source 11
SGF 2013 Finding the Gold in Your Data: An Overview of Data Mining David A. Dickey source 16
SGF 2013 Models for Ordinal Response Data Robin High source 16
SGF 2013 Parallel Multistart Nonlinear Optimization with PROC OPTMODEL Edward P. Hughes,
Tao Huang,
Yan Xu		 source 12
SGF 2013 Smarter Grid Operations with SAS/OR Arnie de Castro,
Greg Link		 source 12
SGF 2013 The Hospital Game: Optimizing Surgery Schedules to Save Resources, and to Save Lives Andrew S. Pease,
Ayesgul Peker		 source 14
SGF 2013 Using PROC FCMP in SAS System Development: Real Examples Xiyun Wang,
Yves DeGuire		 source 10
NESUG 2012 A Model for Extreme Stacking of Data at Endpoints of a Distribution Robert J. Gallop 8
NESUG 2012 Using SAS/OR for Automated Test Assembly from IRT-Based Item Banks Yung-Chen Hsu,
Tsung-hsun Tsai		 5
PHUSE EU 2012 The Logic and Logistics of Logistic Regression, Including New Features in SAS 9.2 Lawrence Rasouliyan source
presentation source		 16
MWSUG 2012 Modeling Complex Survey Data Taylor Lewis 16
MWSUG 2012 Models for Ordinal Response Data Robin High 11
WUSS 2012 Moving Beyond Caveman Communication to Explain the Statistics Behind Your Model:So Easy a PhD Can Do It! Kari Kelso source 9
WUSS 2012 PROC FREQ Is More Than Just Simply Generating a 2-by-2 Table Wuchen Zhao source 11
SGF 2012 Beyond Binary Outcomes: PROC LOGISTIC to Model Ordinal and Nominal Dependent Variables Eric P. Elkin source 8
SGF 2012 Black Box PROCs: PROC LOGISTIC Discovered Isabel H. Perry source 7
SGF 2012 Bringing Optimization to the Business: Interfacing SAS/OR with SAS Stored Processes, Microsoft Excel, SAS Enterprise Guide, SAS Forecast Studio, and Microsoft Project Andrew S. Pease source 15
SGF 2012 Customizing ODS Graphical Output for SAS/STAT Procedures Yang Xiao,
Xiangxiang Meng		 source 9
SGF 2012 Effect Modification, Confounding,Hazard Ratio, Distribution Analysis, and Probability of Non-normal Data for Head Neck Cancer Manojkumar B Agravat source 40
SGF 2012 Enhanced Data Analysis Using SAS ODS Graphics and Statistical Graphics Patricia A. Berglund source 20
SGF 2012 Formation of Optimum Accountable Care Organizations (ACOs) Leveraging SAS/OR Khasha Dehnad source 8
SGF 2012 Introduction to Predictive Modeling with Examples David A. Dickey source 14
SGF 2012 New Features in SAS/OR 12.1 Edward P. Hughes,
Manoj Chari		 source 11
SGF 2012 SAS Tools for Cost-Effective and High-Quality Clinical Trial Reporting Paul J. Novotny,
Angelina Tan,
Nathan R. Foster,
Jeff A. Sloan		 source 10
SCSUG 2011 PROC SURVEYFREQ: Why Do a Three Way Table in SAS When We Want Two Way Table Information? Hemalkumar Mehta source 14
SESUG 2011 Analysis of a Binary Outcome Variable Using the FREQ and LOGISTIC Procedures Arthur X. Li source 18
SESUG 2011 JMP Analytics Applied in Diagnostic Radiology and Neurosurgery Trauma Research Melvin T. Alexander source 18
SESUG 2011 Tailoring Logistic Regression Model Analyses with the ODDSRATIO Statement in PROC LOGISTIC Taylor Lewis source 8
WUSS 2011 Beyond Breslow-Day: Homogeneity Across R x C Tables Ginny Lai source 7
PharmaSUG 2011 A Modular Approach of Reporting Meta Analysis Statistics Using Forest Plots Vikash Jain source 8
PharmaSUG 2011 Classification of frequent snoring from routine medical examinations using the NHANES Database Barry W. Row source 11
PharmaSUG 2011 CONTRAST and ESTIMATE Statements Made Easy: The LSMESTIMATE Statement Kathleen Kiernan,
Randy Tobias,
Phil Gibbs,
Jill Tao		 source 19
PharmaSUG 2011 FAQ: Issues with Efficacy Analysis of Clinical Trial Data Using SAS Sandeep Sawant,
Nehan Mohan		 source 5
PharmaSUG 2011 Formulas Calculating Risk Estimates and Testing for Effect Modification and Confounding Manojkumar B Agravat source 44
SGF 2011 A Goal Programming Approach to Strategic Bank Balance Sheet Management Machiel F. Kruger source 11
SGF 2011 CONTRAST and ESTIMATE Statements Made Easy: The LSMESTIMATE Statement Kathleen Kiernan,
Randy Tobias,
Phil Gibbs,
Jill Tao		 source 19
SGF 2011 Contrast Statements for Binary Responses: Comparing and Contrasting with PROC GLIMMIX Jeffrey M. Gossett,
Mary Aitken,
Beverly K. Miller,
Christopher J. Swearingen		 source 10
SGF 2011 Linear Optimization in SAS/OR Software: Migrating to the OPTMODEL Procedure Robert C. Pratt,
Edward P. Hughes		 source 21
SGF 2011 Logit Models in Practice: B, C, E, G, M, N, O, ... Joseph C. Gardiner,
Zhehui Luo		 source 20
SGF 2011 MCPOWER: a Flexible Macro Suite for Generating Monte Carlo Power Estimates for Linear, Logistic, and Poisson Regression Models Ken Kleinman source 5
SGF 2011 New Features in SAS/OR 9.3 Edward P. Hughes,
Manoj Chari		 source 16
SGF 2011 Optimization of Gas-Injected Oil Wells Robert N. Hatton,
Ken M. Potter		 source 11
SGF 2011 The Final Frontier: A SAS Approach to Data Envelopment Analysis Sabah Sadiq source 7
SGF 2011 Using SAS Procedures FREQ, GENMOD, LOGISTIC, and PHREG to Estimate Adjusted Relative Risks: A Case Study Jiming Fang source 11
SGF 2011 Using SAS to Model and Forecast Greenhouse Gas Abatement Cost Curves Lorry Hardt Jr.,
Keith Renison		 source 10
WUSS 2010 Dummy Coding for Dummies Kathryn Martin source 10
MWSUG 2010 Evaluation of Methods to Determine Optimal Cut Points for Predicting Mortgage Default Valentin Todorov,
Douglas Thompson		 11
PharmaSUG 2010 Graphics Annotation: Tricks to determine the coordinates while using graphics/procedure output area as coordinate systems value Sandeep Sawant 8
PharmaSUG 2010 SAS Programmer's check list-Quick checks to be done before the statistical reports go off the SAS Programmer's table Thomas T. Joseph 7
SGF 2010 A Network Optimization Solution Using SAS/OR Tools for the Department of the Army Branching Problem Michael C. Grierson source 12
SGF 2010 Creating Forest Plots from Pre-computed Data Using PROC SGPLOT and Graph Template Language Zoran Bursac source 9
SGF 2010 Determining Optimal Cash Allocation at ICICI Bank Branches with SAS Enterprise Guide and SAS/OR Software Sandipan Ray source 13
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 Nonlinear Optimization in SAS/OR: Migrating from PROC NLP to PROC OPTMODEL Tao Huang,
Edward P. Hughes		 source 21
SGF 2010 Using Recycled Predictions for Computing Marginal Effects Zhongmin Li,
Geeta Mahendra		 source 10
SESUG 2009 A Logistic Regression Model to Predict Freshmen Enrollments Vijayalakshmi Sampath,
Andrew Flagel		 source 12
SESUG 2009 A New Effect Modification P Value Test Demonstrated Manojkumar B Agravat source 14
SESUG 2009 Industrial Strength Analytics: A Brief Overview of SAS/OR Garland D. Maddox Jr. source 5
SESUG 2009 Short, Sweet and Simple ... how to do more with less in SAS Brian Spruell source 6
SESUG 2009 The Use of SAS in Meta-Analysis Ryan C. Butterfield source 13
MWSUG 2009 Decision Making Using PROC OPTMODEL Joseph Czyzyk 8
NESUG 2009 Formatting Tips and Techniques for Printable Excel Tables Created with the SAS Excel XP ODS Tagset and PROC REPORT Kathy Hardis Fraeman 14
WUSS 2009 Using Recycled Predictions for Estimating Marginal Effects Geeta Mahendra,
Zhongmin Li		 source 9
PharmaSUG 2009 Generating Model Based Subgroup Analysis Using SAS Procedures Tracy Lin,
Jie Huang		 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 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 Image is Almost Everything: Displaying Statistics Via ODS R. Scott Leslie source 8
SGF 2009 New Features in Optimization with SAS/OR Edward P. Hughes,
Trevor D. Kearney		 source 19
SGF 2009 Using the SAS/OR OPTMODEL Procedure to Assign Students to Schools in the Wake County Public Schools System Ivan Oliveira,
Charles Dulaney,
Robert C. Pratt		 source 14
WUSS 2008 Demystifying Popular SAS Procedures. Lisa Smith source 17
WUSS 2008 Image is Almost Everything: Displaying Statistics Via ODS R. Scott Leslie source 5
SESUG 2008 Two SAS macros for DIF Analysis Shiqi Hao source 10
PHUSE EU 2008 A Collection of SAS Macros to Calculate Odds Ratios using Spline Regression Martin Gregory source 9
PHUSE EU 2008 Run Forest ! Run ! Create a flexible Forest Plots with SAS Enterprise Guide. Emmanuel Bourmaud source 12
NESUG 2008 Try, Try Again: Replication-Based Variance Estimation Methods for Survey Data Analysis in SAS 9.2 Pushpal K. Mukhopadhyay 16
PharmaSUG 2008 Automated SAS Macro for Adverse Event Logistic Regression Analysis Suhas R. Sanjee 8
PharmaSUG 2008 Joint Repair: A Statistical Analysis of Patient Data Grant Johnson 20
PharmaSUG 2008 The Logic and Logistics of Logistic Regression Lawrence Rasouliyan,
Dave P. Miller		 14
SGF 2008 How to Use SAS to Fit Multiple Logistic Regression Models Anpalaki J. Ragavan source 13
SGF 2008 Ordered Weight Averaging in SAS: An MCDM Application Ali Emrouznejad source 5
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
SGF 2008 Whats New in Optimization with SAS/OR Edward P. Hughes,
Trevor D. Kearney		 source 16
NESUG 2007 EZLID: A SAS Macro for Local Item Dependence Assessment Yung-Chen Hsu,
Tsung-hsun Tsai		 10
NESUG 2007 PROC LOGISTIC: The Logistics Behind Interpreting Categorical Variable Effects Taylor Lewis 7
PharmaSUG 2007 Graphing Estimates of Regression Models for Discrete and Limited Dependent Variables Jianming He,
David Budd		 10
PharmaSUG 2007 SAS Markov Chain Monte Carlo (MCMC) Simulation in Practice Shi-Tao Yeh,
Scott D Patterson		 20
SGF 2007 Alternatives for Analysis of Complex Sample Surveys: A Comparison of SAS, SUDAAN, and AM Software Bethany A. Kromrey,
Jeffrey D. Bell-Ellison		 source 10
SGF 2007 Optimization with SAS/OR--What It Is, What's New, and How It Adds Value Trevor Hughes,
Ed Kearney		 source 12
SGF 2007 Using SAS Macros to Produce Tables for Publication from SAS-Callable SUDAAN Roger P. Pickering source 10
PNWSUG 2006 You Can't Stop Statistics: SAS/STAT Software Keeps Rolling Along Maura E. Stokes,
Robert N. Rodriguez		 32
MWSUG 2006 Illustrating generation of MSWord tables via HTML with the %cattable and %contable macros Matthew T. Karafa 6
SESUG 2006 Combining PROC GENMOD Models with Multinomial Outcomes Using PROC MIANALYZE Marie Gantz source 7
WUSS 2006 Hierarchical Logistic Regression Modeling with SAS GLIMMIX Jian Dai,
Zhongmin Li,
David Rocke		 source 9
WUSS 2006 PROC GENMOD with GEE to Analyze Correlated Outcomes Data Using SAS Tyler C. Smith,
Besa Smith		 source 14
WUSS 2006 The Logic and Logistics of Logistic Regression Lawrence Rasouliyan,
Dave P. Miller		 source 14
NESUG 2006 Logistic Regression Basics Joseph J. Guido,
Paul Winters,
Adam Rains		 7
NESUG 2006 Survey Logistic Regression: Some SAS-SUDAAN Comparisons Xiuhua Chen 7
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 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 Exploiting the Link Between the Wilcoxon-Mann-Whitney Test and a Simple Odds Statistic Ralph G. O'Brien,
John M. Castelloe		 source 12
SUGI 2006 Fixed Effects Regression Methods in SAS Paul D. Allison source 20
SUGI 2006 Using SAS to Investigate Effect Modification Peter H. Van Ness,
Heather G. Allore		 source 10
SUGI 2006 You Can't Stop Statistics Maura E. Stokes,
Robert N. Rodriguez		 source 32
NESUG 2005 The Big Four: Analyzing Complex Sample Survey Data Using SAS, SPSS, STATA, and SUDAAN Arlene B. Siller,
Linda Tompkins		 7
PharmaSUG 2005 Using Procedure-Based ODS Data Components in Statistical Reporting Vincent J. Faber 10
SUGI 2005 Contrasting Programming Techniques for Summarizing Voluminous SAS Output Using the SAS Output Delivery System (ODS) Stuart D. Long source 17
SUGI 2005 Parameterizing Models to Test the Hypotheses You Want: Coding Indicator Variables and Modified Continuous Variables David J. Pasta source 20
SUGI 2005 Using Procedure-Based ODS Data Components in Statistical Reporting Vincent J. Faber source 10
SUGI 2005 Using SAS to Estimate Proportional Odds Ratio Model for Meta-Analysis of Diagnostic Tests Mir S. Siadaty,
Jianfen Shu		 source 10
SUGI 2005 Using the Proportional Odds Model for Health-Related Outcomes: Why, When, and How with Various SAS Procedures Marc Gameroff source 8
NESUG 2004 Contrasting programming techniques for summarizing voluminous SAS output using the SAS Output Delivery System (ODS) (PROC FREQ as an example) Stuart D. Long,
Lawrence Park		 10
NESUG 2004 Making Data Useful Again: The Full Monte Suzanne Cross,
Tim Leso		 7
WUSS 2004 Beyond Binary Outcomes: PROC LOGISTIC to Model Ordinal and Nominal Dependent Variables Eric P. Elkin source 8
WUSS 2004 Contrasting programming techniques for summarizing voluminous SAS output using the SAS Output Delivery System (ODS) (PROC FREQ as an example) Stuart D. Long,
Lawrence Park		 source 16
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 Analysis of Complex Sample Survey Data Patricia A. Berglund 7
MWSUG 2004 Contrasting Programming Techniques for Summarizing Voluminous SAS Output Using the SAS ODS Stuart D. Long,
Lawrence Park		 17
MWSUG 2004 Presenting the Binary Logit Model Effectively using SAS Hun Myoung Park 11
SUGI 2004 An Introduction to Matching and Its Application Using the SAS System Jayawant N. Mandrekar,
Sumithra J. Mandrekar		 source 9
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
WUSS 2003 Getting Started with PROC LOGISTIC Andrew H. Karp source 6
WUSS 2003 Logistic regression model-building strategies for predicting regular mammography screening adherence among uninsured immigrant women Jesse Albert Canchola,
Regina Otero-Sabogal,
Desiree Owens,
Farzaneh Tabnak		 source 6
WUSS 2003 Presenting Logistic Regression Models to Non-Statisticians: Adjusted Probabilities and Adjusted Risk Ratios David J. Pasta,
Miriam G. Cisternas		 source 4
WUSS 2003 Statistical Analysis of Gene-Environment Data Jimmy Thomas Efird source 3
WUSS 2003 Using SAS for Classical Item Analysis and Option Analysis Chong Ho Yu,
Josephine Wai-chi Wong		 source 6
SESUG 2003 Contrasting programming techniques for summarizing voluminous SAS output using the SAS Output Delivery System (ODS) (PROC FREQ as an example) Stuart D. Long,
Lawrence Park		 source 10
SESUG 2003 Management of CABG Patient Mortality Using SAS Logistic Regression by Cohorts: Age, Sex and Cleveland Clinic defined risk factors Five years of data and analysis compressed onto a 3 X 5 pocket guide Lucinda Jenkins,
Bing Li,
Mike Mueller,
Steve Hadzima		 source 7
NESUG 2003 Forcing SAS/GRAPH Software to Meet My Statistical Needs: A Graphical Presentation of Odds Ratios Richard M. Mitchell 6
SUGI 2003 Estimation of Prevalence Ratios When PROC GENMOD Does Not Converge James A. Deddens,
Martin R. Petersen,
Xiudong Lei		 source 6
SUGI 2003 The Use of Geographic Information Systems to Investigate Environmental Pollutants in Relationship to Medical Treatment Patricia B. Cerrito,
Robert Forbes,
George R. Barnes		 source 6
WUSS 2002 Doing More with Proce FREQ Using Options and ODS Richard Severino source 13
PharmaSUG 2002 Macros for Model Building, Summarizing, and Displaying Results of Stepwise Logistic Regressions Lori S. Parsons 6
PharmaSUG 2002 Performing Logistic Regression on Survey Data with the New SURVEYLOGISTIC Procedure Anthony B. An 10
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 Fast and Easy Ways to Annoy a SAS Programmer: A Statistician's Revenge! Richard M. Mitchell source 10
SUGI 2002 Fast and Easy Ways to Annoy a Statistician: The Sharing and Presentation of Data Between a SAS Programmer and a Statistician Richard M. Mitchell source 10
SUGI 2002 Macros for Model Building, Summarizing, and Displaying Results of Stepwise Logistic Regressions Lori S. Parsons source 6
SUGI 2002 Performing Logistic Regression on Survey Data with the New SURVEYLOGISTIC Procedure Anthony B. An source 9
SUGI 2002 SAS Tools for Meta-analysis Robert M. Hamer,
Pippa M. Simpson		 source 6
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 Making Sense of PROC TABULATE Jonas V. Bilenas 5
SESUG 2001 GETTING STARTED WITH PROC LOGISTIC Andrew H. Karp source 5
SESUG 2001 Supplier Management with SAS Supply Chain Solutions Edward P. Hughes source 4
SCSUG 2001 Getting Started with PROC LOGISTIC Andrew H. Karp 5
SCSUG 2001 Supplier Management with SAS Supply Chain Solutions Edward P. Hughes 4
SEUGI 2001 Web clickstream analysis to understand customer behaviour [presentation] Erika Blanc,
Paolo Giudici		 source 21
SUGI 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 source 10
SUGI 2001 Getting Started with PROC LOGISTIC Andrew H. Karp source 5
SCSUG 2000 U. S. Air Force Has New IDEAS for Information Delivery Eddie Stevens,
Mary G. Crissey		 8
SESUG 2000 Performing Exact Logistic Regression with the SAS R /AD System Robert E. Derr source 10
NESUG 2000 Getting Started with PROC LOGISTIC Andrew H. Karp 5
WUSS 2000 Analyzing Multiple Health Outcomes Using the SAS System's PROC CATMOD Besa Smith source 5
WUSS 2000 Getting Started with PROC LOGISTIC Andrew H. Karp source 5
WUSS 2000 PROC FREQ: It's More Than Counts Richard Severino source 10
SEUGI 2000 SAS Software for the Analysis of Epidemiologic Data [presentation] Hans-Peter Altenburg source 39
PharmaSUG 2000 An Alternative to the Odds Ratio: A Method for Comparing Adjusted Treatment Group Effects on a Dichotomous Outcome P. Chris Holland 5
SUGI 2000 Forcing SAS/GRAPH Software to Meet My Statistical Needs: A Graphical Presentation of Odds Ratios Richard M. Mitchell source 6
SUGI 2000 Getting Started with PROC LOGISTIC Andrew H. Karp source 5
SUGI 2000 PROC FREQ: It's More Than Counts Richard Severino source 10
WUSS 1999 Polychotomous Logistic Regression and the Creation of Odds Ratios and Confidence Intervals Using the SAS PROC CATMOD Besa Nushi source 5
NESUG 1999 Modeling Customer Choice David R. Roberts 6
MWSUG 1999 Using Logistic Regression to Predict Customer Retention Andrew H. Karp 5
MWSUG 1999 Using PROC MIXED in Hierarchical Linear Models: Examples from two- and three-level school-effect analysis, and meta-analysis research Sawako Suzuki,
Ching-Fan Sheu		 8
SEUGI 1999 Improving manufacturing efficiency with optimisation techniques Andrej Pajenk,
Anton Cizman,
Samo Cerc		 source 7
MWSUG 1998 An Introduction to Binary Logistic Regression Linda M. Quinn 8
WUSS 1998 Getting Started with PROC LOGISTIC Andrew H. Karp source 5
NESUG 1998 A Smart Guide to Dummy Variables: Four Applications and a Macro Susan B. Garavaglia 10
NESUG 1998 Information Theory Makes Logistic Regression Special Ernest S. Shtatland 4
NESUG 1998 Using Logistic Regression to Predict Customer Retention Andrew H. Karp 5
SESUG 1998 The Replication Method for Estimating Sampling Errors, Principles, and Software David Morganstein,
J. Michael Brick		 5
SEUGI 1998 Simulation of the probability of disease due to a toxic release Fuming Wu,
Huei Wang,
Raymond A. Gibley,
Wanzer Drane		 source 5
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
WUSS 1997 Logistic Regression Modeling in Complex Surveys: Examples Using LOGITSE SAS Macro Jesse Albert Canchola,
Brian D. Marx,
Joseph A. Catania		 source 10
NESUG 1997 Saving Trees and Time - A SAS Macro for Testing and Reporting the Association Between Multiple Candidate Variables and a Single Binary Variable Christianna S. Williams 9
MWSUG 1997 Enhancing the Output from PROC LOGISTIC Bharat K. Thakkar,
Kwan Hur,
Charles A. Oprian,
William G. Henderson,
Sharon Urbanski		 6
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
SEUGI 1997 Conventional and unconventional graphs in SAS Julian Singer source 8
SUGI 1997 An Experiment Analysis System for Fixed and Random Effects in OverDispersed Binomial Responses in Semiconductor Manufacturing Jose G. Ramirez,
Randall S. Collica		 source 6
SUGI 1997 Getting Started with PROC LOGISTIC Andrew H. Karp source 5
SUGI 1997 Odds Ratios in a Tabular Presentation Stephen M. Noga,
Dingyi Zhao		 source 6
SCSUG 1996 Getting Started with PROC LOGISTIC Andrew H. Karp 5
SESUG 1996 Getting Started with PROC LOGISTIC Andrew H. Karp 5
WUSS 1996 Logistic Regression: From SAS Coding to Statistical Interpretation Elizabeth Li source 9
SEUGI 1996 Graphical aspect of meta-analysis using SAS/GRAPH software and its specific annotate Angelo Tinazzi,
Fabrizio Carinci,
Valter Torri		 source 15
SUGI 1996 Using the SAS System to Detect Differential Item Functioning James A. Penny source 6
MWSUG 1995 An Introduction to Binary Logistic Regression Linda M. Quinn 8
NESUG 1995 Getting Started with PROC LOGISTIC Andrew H. Karp 5
NESUG 1995 How to Put Almost Anything into a PROC TABULATE Cell Michael E. Tomb 2
NESUG 1995 Training in a World of Cost-Cutting and Downsizing Charles E. Shipp,
Kirk Paul Lafler		 6
SESUG 1995 Getting Started with PROC LOGISTIC Andrew H. Karp 5
SESUG 1995 Training in a World of Cost-Cutting and Downsizing Charles E. Shipp,
Laser Prints Plus		 6
SEUGI 1995 Macro Procedure for Equivalence Testing Francois Montestruc source 16
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 Designer Graphics: Anatomy of Some SAS Macros for Statistical Graphics Michael Friendly source 8
SUGI 1995 Training in a World of Cost-Cutting and Downsizing Charles E. Shipp,
Kirk Paul Lafler		 source 6
WUSS 1994 A Matrix Approach to Log-Linear Data Analysis Using SAS/IML Paul W. Johnson source 3
NESUG 1994 PROC LOGISTIC: A Form of Regression Analysis Edith Flaster 3
NESUG 1994 Using of the PHREG Procedure in a Matched Case-Control Analysis Karin LaPann 4
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 Resampling Using SAS/IML Software Some Medical Applications Gina Joubert source 8
SUGI 1994 Application of Random-Effects Model for Categorical Data to Antiemetic Clinical Trials in Cancer Patients Regina Louie,
Alex Yaroshinsky		 source 5
WUSS 1993 A Macro for Personalized Odds Ratios Alice Pressman,
K. L. Stone,
Estie Hudes,
J. L. Tao		 source 4
MWSUG 1993 Designer Graphics - Anatomy of Some SAS Macros for Statistical Graphs Michael Friendly 8
MWSUG 1993 Graphical Methods for Categorical Data Michael Friendly 7
SEUGI 1993 The Analysis of Repeated Measures Designs Using the SAS System Alun Bedding source 9
SUGI 1993 Using SAS/IML Software to Generate Odds Ratios and Associated Intervals Based on Logistic Regression Output Catherine O. Cowie,
Danita D. Byrd-Hol,
Keith F. Rust		 source 6
SCSUG 1992 Calculating the Odds Ratio and Goodness of Fit Statistics for Logistic Regression Models Using PROC LOGISTIC Chuan-Chuan C. Wun 19
NESUG 1992 Principles of Logistic Regression in Radiation Oncology J. Efird,
F. Pardo,
P. Okunieff,
D. Shoenfeld,
H. Aronen		 10
NESUG 1992 Using Macros to Create Parameter Driven Procedures that Summarize and Present Statistical Output in Tabular form John Wenston,
Ralph D'Agostino Jr.,
Kimbery Dukes		 6
SEUGI 1992 Managing Time and Resources Enterprise-wide Project Management Software Helen Hardenbergh source 3
SUGI 1992 Graphical Methods for Categorical Data Michael Friendly source 7
SEUGI 1991 Attributable Risk Estimation Using SAS/STAT Software Olaf Gefellar source 8
SUGI 1991 A Macro to Create a SAS Data Set Containing Commonly Reported Statistics for the Analysis of Multiple 2 x 2 Tables Suzanne Edwards,
John Henry King,
Gary G. Koch		 source 4
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
NESUG 1990 Exact Nonparametric Inference: Theory, Applciations and Software Cyrus R. Mehta 16
SEUGI 1989 Metaanalysis Objectives And Methods Jean-Claude Peyrieux source 6
SUGI 1989 Expected Variation of Study-Specific Vaccine Efficacy Estimates Claire V. Broome,
Lee H. Harrison,
Allen W. Hightower		 source 3
SUGI 1989 Learning C with the SAS/C Compiler, Student Edition Gary H. Merrill,
Dee Stribling		 source 7
SUGI 1989 SAS/OR Software as a Decision Support Tool for the PC Charles Ray Walters source 5
SUGI 1988 Exact and Monte Carlo Methods for Computing Non-Parametric Significance Tests Cyrus R. Mehta,
Nitin R. Patel,
Pralay Senchaudhuri		 source 6
SUGI 1988 Logit Models for Ordered Categorical Response Data Alan Agresti source 9
SUGI 1988 Partial Proportional Odds Models and the LOGIST Procedure Frank E. Harrell Jr.,
Bercedis L. Peterson		 source 5
SUGI 1988 Statistics for Ordered Categorical Data Thomas O'Gorman,
Robert F. Woolson		 source 7
SUGI 1987 Screening for Potential Confounders in an Epidemiologic Analysis Linda Williams Pickle source 4
SUGI 1987 Some Applications of PROC MATPAR: Match Pair Partial Correlation Procedure Chun Chen,
Robert E. Johnson		 source 6
SUGI 1986 Progress Towards SAS/OR Software for the Microcomputer Marc-David Cohen source 9
SUGI 1986 SAS/OR Software - A Decision Support System Prototype for Network Problems Marc-David Cohen source 10
SUGI 1985 Analyzing Tables with Ordered Categories Ginger Caldwell,
John D. Smith		 source 6
SUGI 1985 SAS Software for Stratified Analysis William M. Stanish source 6
SUGI 1984 A General Woolf-Haldane/Mantel-Haenszel Procedure for Dichotomous or Polychotomous Exposure Variables and for Any Number of Stratification/Control Variables Philip N. Gallagher Jr.,
William M. Haenszel		 source 3
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 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 Using SAS and FORTRAN to Produce Mantel-Haenszel Statistics Caroline A. Macera,
Deborah A. Truesdale		 source 4
SUGI 1981 Relative Risk Estimation from Epidemiologic Studies of Matched Sets Elizabeth J. Martin,
Judith H. Mopsik,
Linda Williams Pickle		 source 5
SUGI 1980 Automated Analysis of Case-Control Data Using the SAS System Elizabeth J. Martin,
Linda Williams Pickle		 source 6
SUGI 1980 Odds Ratio Estimation for Polychotomous Exposures Elizabeth J. Martin,
Linda Williams Pickle		 source 3
SUGI 1979 Uses of SAS for Corporate Operations Research Robert L. Anderson source 1
SUGI 1978 Maximum Likelihood Estimation of the Multivariate Logistic Martha McCrate,
Michael A. Province,
Reimut Wette		 source 3

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