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342 papers and 6 presentations; 335 titles.

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Conference × Year × Title × Authors Extras Pages
WUSS 2026 Beyond a P-Value Vending Machine: Becoming a Research Partner, Not a Service Provider Mehrnaz Siavoshi source 10
WUSS 2026 The Living Dead in Your Cohort: Immortal Time Bias Detection and Correction in SAS Mehrnaz Siavoshi source 14
PharmaSUG CN 2026 A Standardized Programming Framework for Daily Dose Dataset Construction from Multi-Source Clinical Data Xianjun Li,
Chengye Lu		 source 10
PharmaSUG CN 2026 Handling Missing Data in Analgesia Clinical Trials and Corresponding SAS Implementation Jingbo Zhu,
Jiehan Zhang		 source 17
PharmaSUG CN 2026 Health Technology Assessment (HTA) Under EMA Framework: From Emerging to Mandatory Submission Jun Zhai source 7
PharmaSUG CN 2026 Safety Estimands and Analysis Dataset Design: Advancing Safety Evaluation in Clinical Trials Kun Ren,
Zeyu Guang		 source 11
PharmaSUG 2026 A Statistical Programmer-s Guide to Tipping Point Analysis in SAS Ang Xu source 9
PharmaSUG 2026 Beyond WHODrug: Insight into Concomitant Medication Data Analysis Song Liu,
Martin Nielsen,
Rambabu Sura		 source 9
PharmaSUG 2026 Construction and Evaluation of External Controls Using Propensity Score Methods Bala Niharika Pillalamarri,
Yayu Li,
Hongbing Jin		 source 14
PharmaSUG 2026 Contrast Effects in Curated Observational Data Shankar Srinivasan,
Helen Guo,
Yvonne Buttkewitz		 source 16
PharmaSUG 2026 Corticosteroids in severe COVID-19 across molecular endotypes and vaccination status: an Emulated Target Trial approach to benchmark to and extend upon findings from RECOVERY Xi Jiang,
Scott McClain,
Ella Pavlechko,
Varunraj Valsaraj		 source 10
PharmaSUG 2026 Embracing Novel Approaches to Automated Causal Inference Framework Laura Watson,
Sherrine Eid		 source 15
PharmaSUG 2026 Tipping Point Analysis: An Illustration of Sensitivity Analysis on Non-Administrative Censoring for Progression-Free Survival (PFS) Lihui Deng,
Kylie Fan,
Xiaoting Qin		 source 7
PHUSE US 2026 A Practical Approach to Causal Inference Sherrine Eid,
Laura Watson		 source
presentation source		 10
PHUSE US 2026 Building the Information Infrastructure Required for AI with Human in the Loop [presentation] Tomás Sabat Stofsel source 53
PHUSE US 2026 Defining Time Zero: Evaluating Index Line Selection Methods in External Control Arms (ECAs) Peishan(Jenny) Han,
Lorraine Fang		 source
presentation source		 5
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 US 2026 Estimand-Aligned Multiple Imputation Strategies in CNS Trials with Complex Intercurrent Events Veera Thota,
Ian Lees		 source
presentation source		 6
PHUSE US 2026 Framework for Incorporating Estimands within the Statistical Analysis Plan Inderjeet Arora source
presentation source		 9
PHUSE US 2026 From Tables to Text: Revolutionizing CSR Development with Generative AI Eric Zloty source
presentation source		 10
PHUSE US 2026 Is Complexity Worth It? A Case Study Comparing Multiple Imputation Strategies Elnaz Ghadimi,
David Bushnell		 source
poster source		 4
PHUSE US 2026 Is There Really Any Benefit to Stratified Randomisation in Practice? Pavankumar Bhagat source
presentation source		 9
PHUSE US 2026 Practical Survival Analysis Techniques for Clinical Trials Using SAS Xue Ding,
Tianchen Xu		 source
presentation source		 10
PHUSE US 2026 Robust Causal Inference in Real-World Evidence Studies with Double Machine Learning Yilun Huang,
Jing Dai		 source
presentation source		 5
PHUSE APAC 2026 Advancing Clinical Trial Analysis with Trimmed Means: Estimands, Intercurrent Events, and Regulatory Alignment Prasanth Palanisamy source
presentation source		 9
PHUSE APAC 2026 Beyond Log-Rank: Advanced Survival Analysis for Non-Proportional Hazards in Oncology Trials Jagdish Nikam source
poster source		 7
PHUSE APAC 2026 Connecting Open-Source and Enterprise Software: Enhancing Phase III Clinical Trial Design Through R Integration in East Horizon Pradip Maske,
Anoop Rawat		 source
presentation source		 6
PHUSE APAC 2026 Crafting a recipe for success : Aligning Target Product Profiles and study design to ensure statistical significance translates to clinical relevance and role of DGF Soumitra Kar,
Novo Nordisk GBS		 source
presentation source		 9
PHUSE APAC 2026 Development of Statistical Scientists for Pharmaceutical Drug Development at India Global Capability Centres Suresh Chenji source
presentation source		 6
PHUSE APAC 2026 Elastic Net Meets BART: A Hybrid Virtual Twins Approach for Reliable Subgroup Identification Alexis Bernard Dalam source
presentation source		 10
PHUSE APAC 2026 Estimands Framework Through the Eye of a Statistical Programmer Shraddha Ganoo,
Kinjal Pandat		 source
presentation source		 9
PHUSE APAC 2026 Estimation of the Hypothetical Estimands using Longitudinal version of the TMLE Shreya Wahi source
presentation source		 8
PHUSE APAC 2026 External Comparator Studies in the Era of Real-World Data Vishal Goriya,
Anshul Sinha,
Gerd Rippin		 source
presentation source		 5
PHUSE APAC 2026 Illustrating treatment switching using Rank preserving structural failure time model in Oncology study Swarupa Changan source
presentation source		 11
PHUSE APAC 2026 Invisible Influences: Estimands, Assumptions and Sensitivity in Inflammation & Immunologic Trial Interpretation Sukanya Erramachetty Subramanyam source
presentation source		 8
PHUSE APAC 2026 Solving the Fragmentation Challenge in RA Trials: Deriving deeper insights Umayal Annamalai,
KiranKumar Vyas		 source
presentation source		 13
PHUSE APAC 2026 Swimmer Plots in Clinical Programming Implementation and Visualization Using SAS and R Ramya V. Kini,
Vinay S		 source
poster source		 6
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
PHUSE APAC 2026 Tipping Point Analysis in R and SAS: A Comparative Approach to Handling Missing Data in Clinical Research Sushil Kale,
Jeet Agrawal		 source
poster source		 7
PHUSE APAC 2026 Vision to Decision: An Ocular case study on Estimand Deepak Kumar source
presentation source		 5
PHUSE EU 2025 Bridging the Gap: Translating Intercurrent Events into Analysis-Ready ADaM Datasets Meghna Diedrich source
poster source		 9
PHUSE EU 2025 Cracking the Curve: Unlocking Clinical Insights with Ridgeline Plots Mariam Babayan,
Rafik Ghazaryan		 source
presentation source		 6
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
PHUSE EU 2025 Inverse Probability Weighting in Multiple Groups: Balancing Baseline Characteristics and Improving Precision of Average Treatment Effect Estimation Dimitris Karletsos source
presentation source		 11
PHUSE EU 2025 Is There Really Any Benefit to Stratified Randomisation Compared to Simple Randomisation with Covariate Adjustment? Pavankumar Bhagat source
presentation source		 9
PHUSE EU 2025 Showcasing a Shiny Tool for Evaluating Biomarkers for Derisking Clinical Trials Stefan Thoma source
presentation source		 9
PHUSE EU 2025 Visualising the Invisible: Patient Journey with Waterfall, Spider and Swimmer Plots Varsha Mithun Patil,
Sunita Poojary		 source
presentation source		 14
PharmaSUG 2025 An End-to-End Workflow for TFL Generation using R: MMRM Applications and Comparative Insights with SAS Kai Lei,
Jiaqiang Zhu,
Margaret Huang		 source 14
PharmaSUG 2025 Calculating exact posterior probabilities and credible intervals from Bayesian borrowing robust mixture priors for binary, count and continuous outcomes in R and SAS Darren Scott,
Armando Turchetta		 source 20
PharmaSUG 2025 Handling Missing Data in External Control Arms: Best Practices, Recommendations, and SAS Code Examples Yutong Zhang source 6
PharmaSUG 2025 Implementation of the inverse probability of censoring weighting (IPCW) Model in Oncology Trials Mei Huang,
Shibani Harite,
Haijun Ma,
Linsong (Athena) Zhang		 source 17
PharmaSUG 2025 Leveraging previous study data for Extension studies: Structuring Subject and Participant Level Analysis datasets using CRF data Priyanka Thumuganti source 7
PharmaSUG 2025 Mastering the Maze of Oncology Endpoints: A Unified SAS Approach for Randomized Controlled Trial Analysis Yuxin Wang,
Kelly Chao,
Wenqing Yu,
Hongbing Jin		 source 11
PharmaSUG 2025 Practical Process in SAS of Using External Controls Hui Mao,
Na Wang,
Lixin Gao		 source 5
PharmaSUG 2025 Promising Zone Designs for Sample Size Re-estimation in Clinical Trials: Graphical Approaches Using SAS Zhao Yang,
Shivani Nanda		 source 18
PharmaSUG 2025 Super Learner for Predictive Modeling and Causal Analysis Honghe Zhao,
Clay Thompson,
Michael Lamm		 source 9
PHUSE US 2025 Advancing Safety Evaluation in Oncology Trials Using Estimands Reshma Radhakrishnan,
Lakshmi Mantha		 source
presentation source		 8
PHUSE US 2025 Learnings from a Multistakeholder Estimands Project: A White Paper Journey [presentation] Matt Baldwin,
Banoo Madhanagopal		 source 18
PHUSE US 2025 More Than a p-Value: Understanding the Differences Between Clinical and Statistical Significance Jasperlynn Kao,
Elnaz Ghadimi		 source
presentation source		 4
PHUSE US 2025 Revolutionising Cancer Trials with Adaptive Designs and Bayesian Analysis Navneet Jha source
presentation source		 11
PHUSE US 2025 SAS Programming approach for adjustment of treatment switching using Two-Stage Method Mani Mudumba source
presentation source		 13
PHUSE US 2025 Transforming Clinical Trials: Leveraging Bayesian Statistics in Innovative Trial Design, Analysis, Applications and Navigating Challenges Jaskaran Singh Saini source
presentation source		 11
PHUSE EU 2024 Innovation of Causal Inferential Frameworks for Biostatistics in Real-World Data and Evidence Anwesha Roy source
poster source		 8
PHUSE EU 2024 Leveraging Bayesian Posterior Probability for Analysing Treatment Effects in Clinical Trials: A Statistical Programmer's Guide Vismaya Kondassam Veedu source
presentation source		 7
PHUSE EU 2024 MAICing Efficient, Flexible and Maintainable Code with Modular Programming Michael Allie source
presentation source		 10
PHUSE EU 2024 Strategies to Improve Understanding of Estimands and Analysis Section of Statistical Analysis Plan Inderjeet Arora source
presentation source		 8
PHUSE EU 2024 Streamlining Complex Analysis: An SAS Macro for Marginal Structural Modelling Amine Khemiri source
presentation source		 6
PHUSE EU 2024 Unveiling the Tipping Point: An In-depth Analysis Varsha Mithun Patil,
Ephicacy Lifescience		 source
presentation source		 8
WUSS 2024 Estimating causal effects of health interventions using instrumental variables Mehrnaz Siavoshi source 7
PharmaSUG CN 2024 Implementation on concentration-QTc modeling Daoqing Li,
Deli Cao		 source 20
PharmaSUG CN 2024 Implementing the treatment policy estimation for continuous variable with multiple imputation Andy Sun source 17
PharmaSUG CN 2024 Programming Perspective: Streamline Estimands, Strategies, and Design ADaM for Estimand Yuqin Wu source 10
PharmaSUG 2024 Bayesian Additive Regression Trees for Counterfactual Prediction and Estimation Michael Lamm source 10
PharmaSUG 2024 Updates on Preparing a BIMO Data Package Elizabeth Li,
Carl Chesbrough,
Inka Leprince		 source 17
PharmaSUG 2024 Win a PS5! How to Run and Compare Propensity Score Matching Performance Across Multiple Algorithms in Five Minutes or Less Catherine Briggs,
Sherrine Eid,
Samiul Haque,
S. Robert Collins		 source 11
PHUSE US 2024 Are Platform Studies the Need of the Hour for Oncology Trials? Vidya Muthukumar source
presentation source		 2
PHUSE US 2024 Comparing the Performance of Propensity Score Matching Algorithms from Multiple Programming Languages Catherine Briggs source
presentation source		 7
PHUSE US 2024 Comparison of Standard Log-Rank Test with Selected Alternatives Elena Valkanova,
Bulat Fatykhov		 source
poster source		 18
PHUSE EU 2023 A Beginner's Guide to Overcome the Attrition Bias in Clinical Research: The Method of Inverse Probability of Attrition Weighting (IPAW) Parichay Srivastava source
presentation source		 9
SESUG 2023 How to use SAS POWER procedure to plan a study Xiaofeng (Steven) Liu source 4
SESUG 2023 Longitudinal Analysis of Marital Therapy's Impact on Intimacy in Heterosexual Couples Yaa Awuah,
Mostafa Zahed		 source 19
SESUG 2023 Wald Tests in Mixed Models - a Warning David A. Dickey source 20
PharmaSUG 2023 Application of Tipping Point Analysis in Clinical Trials using the Multiple Imputation Procedure in SAS Yunxia Sui,
Xianwei Bu,
Yuanyuan Duan,
Yihan Li,
Xin Wang		 source 12
PharmaSUG 2023 Guidelines for the Statistical Analysis in German Dossier Submissions Meiling Gao,
Xi Qian,
Hui Mao		 source 8
PharmaSUG 2023 Sensitivity Analysis for Missing Data Using Control-based Pattern Imputation Jun Feng,
Jingmin Liu		 source 7
PharmaSUG 2023 Statistical Considerations and Methods for Handling Missing Outcome Data in Clinical Trials During the Era of COVID-19 Xi Qian,
Chengfei Lu		 source 11
PharmaSUG 2023 Survival Methods for Crossover in Oncology Trials Brian Mosier source 18
PharmaSUG 2023 Validating novel maraca plots - R and SAS love story Nicole Major,
Srivathsa Ravikiran,
Monika Huhn,
Samvel Gasparyan,
Martin Karpefors		 source 17
PHUSE US 2023 FORESTLY - An R Package to Generate Interactive Forest Plots Bingjun Wang,
Yilong Zhang		 source
presentation source		 14
PHUSE US 2023 Handling Multiple Adaptations in One Clinical Trial Parvee Kumar,
Shrutimita Pokhariyal		 source
presentation source		 6
SESUG 2022 Leading Change: Using Data and Feedback to Launch a Strategic Plan or New Initiative Anne L. Oxenreider source 5
PharmaSUG 2022 Two Methods to Collapse Two Treatment Groups into One Group Kenneth S. Liu,
Ziqiang Chen		 source 6
PHUSE US 2022 Reassure Your Assumptions Using Sensitivity Analysis [presentation] Vadym Kalinichenko source
video		 29
PHUSE EU 2021 Bringing to Light - Analysis Results Metadata v1.0 for Define-XML v2 [presentation] Hrishikesh K S,
Limna Salim		 source
video		 11
PHUSE EU 2021 Statistical Training for Health Technology Assessment Statistical Programmers Anastasia Kokoreva,
William Malbecq		 source
video
presentation source		 7
SGF 2021 Modeling Causal Effects Using SAS/STAT John Amrhein,
McDougall Scientific		 source 21
PHUSE EU 2020 How to Limit Bias in Observational Studies Analysis - Propensity Score Matching Versus Logistic Regression Roxane Debrus source
video
presentation source		 12
SESUG 2020 A Doctor's Dilemma: How Propensity Scores Can Help Control for Selection Bias in Medical Education Deanna Naomi Schreiber-Gregory source 13
SGF 2020 A Doctor's Dilemma: How Propensity Scores Can Help Control for Selection Bias in Medical Education Deanna Naomi Schreiber-Gregory source 13
SGF 2020 A Warning about Wald Tests David A. Dickey source 20
SGF 2020 Bayesian Sequential Monitoring of Clinical Trials Using SAS Matthew A. Psioda source 13
SGF 2020 Causal Effect Estimands: Interpretation, Identification, and Computation Clay Thompson source 20
SGF 2020 Propensity Score Matching with Survey Data Bocheng Jing source 14
SGF 2020 Simulating Data for Complex Linear Models Phil Gibbs,
Kathleen Kiernan		 source 20
SGF 2020 Transdermal Medicine - Challenges and Solutions with SAS Marina Komaroff source 14
PharmaSUG 2020 A Doctor's Dilemma: How Propensity Scores Can Help Control for Selection Bias in Medical Education Deanna Naomi Schreiber-Gregory source 14
PharmaSUG 2020 Preparing a Successful BIMO Data Package Elizabeth Li,
Carl Chesbrough,
Inka Leprince		 source 20
PharmaSUG 2020 Principal Stratum strategy for handle intercurrent events: a causal estimand to avoid biased estimates Andrea Nizzardo,
Giovanni Marino Merlo,
Simona Scartoni		 source 13
PharmaSUG 2020 Risk-based and Exposure-based Adjusted Safety Incidence Rates Qiuhong Jia,
Fang-Ting Kuo,
Chia-Ling (Ally) Wu,
Ping Xu		 source 8
PHUSE US 2020 Data Science Project (Educating for the Future Working Group) Aldir Medeiros Filho,
Sascha Ahrweiler		 source
presentation source		 10
PHUSE US 2020 Handling Missing Data in Clinical Trials: Techniques and Methods Pennidhi Karlakunta,
Naveen Kommuru		 source
presentation source		 9
PHUSE EU 2019 ML07 Interpreting Black-box Machine Learning Models: Real-world Evidence Examples and Application [presentation] Jim Box source 24
PHUSE EU 2019 Multiple imputation as a valid way of dealing with missing data Vadym Kalinichenko source
presentation source		 11
SESUG 2019 ePRO: A View from Statistical Programmer Vijetha Kode,
Saigovind Chenna		 source 18
SESUG 2019 Introduction to Propensity Score Modeling and Treatment Effect Estimation Jason Brinkley source 13
PharmaSUG 2019 Bayesian Methods for Treatment Design in Rare Diseases Xuan Sun,
Ruohan Wang		 source 5
PharmaSUG 2019 Equivalence, Superiority and Non-inferiority with Classical Statistical Tests: Implementation and Interpretation Marina Komaroff source 7
PharmaSUG 2019 F2Plots: Visualizing relative treatment effects in cancer clinical trials Yellareddy Badduri source 9
PharmaSUG 2019 Forest Plots for Beginners Savithri Jajam,
Olesya Masucci		 source 9
PharmaSUG 2019 Practical Perspective in Sample Size Determination Bill Coar source 16
PharmaSUG 2019 Statistical Assurance in SAS: An Introduction and User-s Guide Jonathan L Moscovici,
Milena Kurtinecz		 source 8
PharmaSUG 2019 This Paper focuses on CDISC Questionnaires, Ratings and Scales (QRS) supplements and types of FDA Clinical Outcome Assessments Shrishaila Patil source 10
SGF 2019 Analyzing Structural Causal Models using the CALIS Procedure Banoo Madhanagopal,
John Amrhein		 source 23
SGF 2019 Applying Propensity Score Methods to Complex Survey Data Using PROC PSMATCH Patrick Karabon source 10
SGF 2019 Building a Propensity Score Model with SAS/STAT Software: Planning and Practice Michael Lamm,
Clay Thompson,
Yiu-Fai Yung		 source 24
SGF 2019 Causal Analyses Using Structural Equation Models Banoo Madhanagopal,
John Amrhein		 source 23
SGF 2019 Causal Graph Analysis with the CAUSALGRAPH Procedure Clay Thompson source 21
SGF 2019 Real-World Evidence and Population Health Analytics: Intersection and Application David Olaleye source 16
PHUSE US 2019 A SAS Macro for Variable Ratio Treatment vs. Placebo in Propensity Score Matching Punjita Baranwal,
Prashant Kulkarni		 source
presentation source		 13
PHUSE US 2019 Interactive Exploratory Analysis and Visualization for Late-phase Clinical Data Sheng-Wei Wang,
Casey Yang		 source
presentation source		 9
PHUSE US 2019 Interactive Visualization of SEND Clinical Pathology Data Using R Shiny Kevin Snyder source
presentation source		 8
PHUSE US 2019 Misuse and Misapplication in Statistical Data Analysis - A Topic that Never Goes Out of Style Corinna Miede source
presentation source		 12
PHUSE EU 2018 Enhancing the Application of Real-world Evidence with Episode of Care Analytics David Olaleye,
Lina Clover		 source
presentation source		 13
PHUSE EU 2018 Overlooked Tiny Numeric Representation Errors in SAS May Lead to Substantially Misleading p-Value Ying Zhou,
David Haryanto		 source
presentation source		 11
PHUSE EU 2018 Propensity Score Matching Stephanie Fechtner source
presentation source		 9
PHUSE EU 2018 Sample Size: A Couple More Hints to Handle it Right Using SAS and R Andrii Artemchuk source
presentation source		 11
PHUSE EU 2018 Subpopulation Treatment Effect Pattern Plot (STEPP) for Categorisation of Baseline Characteristics Andrea Parodi,
Dimitri Petratchenko		 source
poster source		 6
MWSUG 2018 Baseline Mean Centering for Analysis of Covariance (ANCOVA) Method of Randomized Controlled Trial Data Analysis Jennifer Scodes 6
MWSUG 2018 Propensity Scores and Causal Inference for (and by) a Beginner Bruce S. Lund 18
WUSS 2018 Oops, I D-I-D It Again! Advanced Difference-in-Differences Models in SAS Margaret Warton,
Melissa Parker		 source 17
PHUSE US 2018 Interim Survival Analysis Across 3 Platforms Venita DePuy source
presentation source		 22
PharmaSUG 2018 Application of Survival Analysis in Multiple Events Using SAS Jane Lu,
David Shen		 source 9
PharmaSUG 2018 Implementing the Rank-Preserving Structural Failure Time Model in SAS and R Bradford J. Danner,
Indrani Sarkar		 source 8
PharmaSUG 2018 Manipulating Statistical and Other Procedure Output to Get the Results That You Need Vincent DelGobbo source 37
SGF 2018 !WRONG PAPER FIEL - WAITING for FIX! Nikki M. Carroll source 9
SGF 2018 Application of Propensity Score Models in Observational Studies Nikki M. Carroll source 9
SGF 2018 Causal Mediation Analysis with the CAUSALMED Procedure Michael Lamm source 20
SGF 2018 Manipulating Statistical and Other Procedure Output to Get the Results That You Need Vincent DelGobbo source 37
SGF 2018 SAS Macros for Computing Causal Mediated Effects in Two- and Three-Wave Longitudinal Models David P. MacKinnon,
Matthew Valente		 source 18
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
SESUG 2017 Propensity Score Methods for Causal Inference with the PSMATCH Procedure Yang Yuan,
Yiu-Fai Yung,
Maura E. Stokes		 source 17
SESUG 2017 Removing the Mask of Average Treatment Effects in Chronic Lyme Disease Research Using Big Data and Sub-Group Analysis Mira Shapiro,
Lorraine Johnson		 source 9
PHUSE EU 2017 Decrypting SDTM Trial Design Datasets for Complex Study Designs Charumathy Sreeraman source
presentation source		 14
PHUSE EU 2017 Futile or Not? An Interim Analysis Case Study Ingrid Franklin source
presentation source		 9
PHUSE EU 2017 Health Technology Assessment PRO Least Squares Mean Difference Programming Techniques Using SAS Yirong Cao,
Siory Traoré		 source
presentation source		 11
PHUSE EU 2017 Visualizing Multiple Endpoints: Extending the Use of Forest Plots in Clinical Trials James R. Johnson,
Mark Jaros		 source
presentation source		 10
WUSS 2017 Propensity Score Methods for Causal Inference with the PSMATCH Procedure Maura E. Stokes source 17
PharmaSUG 2017 Removing the Mask of Average Treatment Effects in Chronic Lyme Disease Research Using Big Data and Sub-Group Analysis Mira Shapiro,
Lorraine Johnson		 source 9
PharmaSUG 2017 Two Roads Diverged in a Narrow Dataset-When Coarsened Exact Matching is More Appropriate than Propensity Score Matching Aran Canes source 7
SGF 2017 Differentiate Effects from the Noise of Promotional Marketing Campaigns Alex Glushkovsky,
Matthew Fabian		 source 9
SGF 2017 Estimating Causal Effects from Observational Data with the CAUSALTRT Procedure Michael Lamm,
Yiu-Fai Yung		 source 18
SGF 2017 Propensity Score Methods for Causal Inference with the PSMATCH Procedure Yang Yuan source 17
SESUG 2016 Surviving the Interim: Insights Into Interim Survival Analyses Venita DePuy source 31
PHUSE EU 2016 Considerations in the Use of Propensity Scoresin Observational Studies Lawrence Rasouliyan,
Estel Plana		 source
presentation source		 17
MWSUG 2016 The Power of Cumulative Distribution Function (CDF) Plot in Assessing Clinical Outcomes Min Chen,
Patricia Kultgen		 6
PharmaSUG CN 2016 Proportion difference and confidence interval based on Cochran-Mantel-Haenszel method in stratified multi-center clinical trial Huiping Zhang 5
WUSS 2016 Did the Protocol Change Work? Interrupted Time Series Evaluation for Health Care Organizations. Carol Conell,
Alexander C. Flint		 source 14
WUSS 2016 Selection Bias: How Can Propensity Score Utilization Help Control For It? Deanna Naomi Schreiber-Gregory source 13
PharmaSUG 2016 What-s the Case? Applying Different Methods of Conducting Retrospective Case/Control Experiments in Pharmacy Analytics Aran Canes source 8
SGF 2016 Personal Lending: Customer Credit and Pricing Optimization Yuri Medvedev source 19
SGF 2016 PROC GLIMMIX as a Teaching and Planning Tool for Experiment Design Walter W. Stroup source
zip		 19
SGF 2016 Using Administrative Databases for Research: Propensity Score Methods to Adjust for Bias Ruth Croxford source 10
SGF 2016 Using Propensity Score Analyses to Adjust for Selection Bias: A Study of Adolescent Mental Illness and Substance Use Deanna Naomi Schreiber-Gregory source 7
MWSUG 2015 Utilizing Propensity Score Analyses to Adjust for Selection Bias: A Study of Adolescent Mental Illness and Substance Use Deanna Naomi Schreiber-Gregory 7
PHUSE EU 2015 Adjusting Long-term Efficacy Estimates when Patients Cross Over to Experimental Treatment Sabine Lauer source
presentation source		 11
PHUSE EU 2015 Bias Reduction in Observational Cohort Studies - Obtaining Matched Cohorts Using Propensity Scores Shelley Fordred,
Victor Kiri		 source
presentation source		 8
PHUSE EU 2015 Facing Your Fear of the Unknown - Handling Missing Data Amanda Reilly source
presentation source		 7
SESUG 2015 A SAS Macro to Investigate Statistical Power in Meta-analysis Jin Liu,
Fan Pan		 source 5
SESUG 2015 An Empirical Comparison of Multiple Imputation Approaches for Treating Missing Data in Observational Studies Yan Wang,
Seang-Hwane Joo,
Jeffrey D. Kromrey		 source 20
PharmaSUG CN 2015 Approaches to Missing Data in the Analysis of SpondyloArthritis International Society (ASAS 20) Response and the Creation of the Related CDISC Compliant Analysis Datasets Christine Joy Dureza 12
PharmaSUG CN 2015 Hands-on Tutorial for Piecewise Linear Mixed-effects Models Using SAS PROC MIXED Qinlei Huang 15
PharmaSUG 2015 Analysis Methods for a Sequential Parallel Comparison Design (SPCD) Harry Haber,
James Zuazo,
Linda LaMoreaux		 source 11
PharmaSUG 2015 Missing Data For Repeated Measures: Single Imputation VS Multiple Imputation Giulia Tonini,
Simona Scartoni,
Camilla Paoli,
Andrea Nizzardo,
Angela Capriati		 source 10
SGF 2015 An Empirical Comparison of Multiple Imputation Approaches for Treating Missing Data in Observational Studies Patricia Rodríguez de Gil,
Shetay Ashford,
Chunhua Cao,
Eun Sook Kim,
Rheta Lanehart,
Reginald Lee,
Jessica Montgomery,
Yan Wang		 source 20
SGF 2015 Causal Analytics: Testing, Targeting, and Tweaking to Improve Outcomes Jason Pieratt source 8
SGF 2015 Kaplan-Meier Survival Plotting Macro %NEWSURV Jeffrey P. Meyers source 20
SGF 2015 The SEM Approach to Longitudinal Data Analysis Using the CALIS Procedure Xinming An,
Yiu-Fai Yung		 source 18
PHUSE EU 2014 Data Challenges in Adaptive Trials Claudio Garutti source
presentation source		 5
PHUSE EU 2014 Multiple Imputation: Better than Single Imputation in Pain Studies Ashik Chowdhury source
presentation source		 12
PHUSE EU 2014 PROC EASTMONITOR - A SAS Add-on for Monitoring Adaptive Clinical Trials Sheetal Solanki,
Ajay Sathe		 source
presentation source		 15
MWSUG 2014 ANCOVA (Analysis of Covariance): A Visual, Intuitive Understanding Michael Senderak 12
MWSUG 2014 Kaplan-Meier Survival Plotting Macro %NEWSURV Jeffrey P. Meyers 20
PharmaSUG 2014 Handling with missing data in clinical trials for time-to-event variables Giulia Tonini,
Simona Scartoni,
Angela Capriati		 source 9
PharmaSUG 2014 Kaplan-Meier Survival Plotting Macro %NEWSURV Jeffrey P. Meyers source 19
PharmaSUG 2014 Risk-Based Approach to Identifying and Selecting Clinical Sites for Sponsor's Preparation for FDA/EMA Inspection Xiangchen (Bob) Cui source 21
SGF 2014 Analyzing Data from Experiments in Which the Treatment Groups Have Different Hierarchical Structures Sharon Lohr,
Peter Schochet		 source 12
SGF 2014 Bayesian Framework in Early Phase Drug Development with SAS Examples Howard Liang source 4
SGF 2014 Sensitivity Analysis in Multiple Imputation for Missing Data Yang Yuan source 12
SGF 2014 Trimmed_t: A SAS Macro for the Trimmed T-Test Patricia Rodríguez de Gil,
Anh P. Kellermann,
Diep T. Nguyen,
Eun Sook Kim,
Jeffrey D. Kromrey		 source 13
PHUSE EU 2013 Oncology Endpoints: An Unexpected Journey Waseem Jugon,
Mijanur Rahman		 source 12
PharmaSUG 2013 Adjusted proportion difference and confidence interval in stratified randomized trials Yeonhee Kim,
Seunghyun Won		 source 8
PharmaSUG 2013 Combining Analysis Results from Multiply Imputed Categorical Data Bohdana Ratitch,
Ilya Lipkovich,
Michael O'Kelly		 source 19
PharmaSUG 2013 Doctoring Your Clinical Trial with Adaptive Randomization: SAS Macros to Perform Adaptive Randomization Jenna Colavincenzo source 9
PharmaSUG 2013 Time to Event Analysis in the Pharmaceutical and Medical Device Industries Helen M. Chmiel,
Evan L. Ritzema		 source 8
SGF 2013 Assessing Drug Safety with Bayesian Hierarchical Modeling Using PROC MCMC and JMP Richard C. Zink source 13
SGF 2013 Doctoring Your Clinical Trial with Adaptive Randomization: SAS Macros to Perform Adaptive Randomization Jenna Colavincenzo source 9
SGF 2013 Missing No More: Using the MCMC Procedure to Model Missing Data Fang K. Chen source 23
SGF 2013 Short-Term Costs of Smoking during Pregnancy: A Geometric Multidimensional Approach Violeta Balinskaite source 11
SESUG 2012 A Randomization Test SAS/IML Program for Making Treatment Effects Inferences for Extensions and Variations of ABAB Single-Case Experimental Designs Patricia Rodríguez de Gil,
John M. Ferron		 source 8
SESUG 2012 A SAS macro to compute effect size (Cohen's d) and its confidence interval from raw survey data Rajendra P source 12
PharmaSUG 2012 A SAS Macro for Biomarker Analysis using Maximally Selected Chi-Square Statistic With Application in Oncology Quan Jenny Zhou,
Bala Dhungana		 source 8
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 Innovative Uses of ODS and GTL Kathy Chen source 12
SGF 2012 Propensity Score Analysis and Assessment of Propensity Score Approaches Using SAS Procedures Rheta E. Lanehart,
Patricia Rodríguez de Gil,
Eun Sook Kim,
Aarti P. Bellara,
Jeffrey D. Kromrey,
Reginald Lee		 source 11
WUSS 2011 Causal Methods for Observational Data Amanda Stevenson source 8
WUSS 2011 Consistency of Treatment Effect cross Regions Yunfeng Li source 6
WUSS 2011 Producing Cumulative Distribution Frequency Figures with Minimal Important Difference Reference Lines to Assess Quality of Life Treatment Effects Xiao Liu source 7
MWSUG 2011 Comparing Over-the-Counter Drug Prices and Availability Using Nonparametric Tests Deanna Naomi Schreiber-Gregory 3
MWSUG 2011 Outlier resistance of multivariate bioequivalence procedures Srinand P. Nandakumar,
Joseph W. McKean		 13
PharmaSUG 2011 Creating Forest Plots Using SAS/GRAPH and the Annotate Facility Amanda Tweed source 7
PharmaSUG 2011 Implementation of Pattern-Mixture Models Using Standard SAS/STAT Procedures Bohdana Ratitch,
Michael O'Kelly		 source 10
PharmaSUG 2011 Statistical Analysis of Adverse Events in Randomized Clinical Trials Using SAS Dongsun Cao,
Xiaomin He		 source 12
SGF 2011 Living with Generalized Linear Mixed Models Walter W. Stroup source 18
NESUG 2010 Macro for Computing Complier-Average Causal Effect of Treatment (CACE) Using Instrumental Variable Method Patricia R. Houck,
Sati Mazumdar,
Benoit H. Mulsant		 3
SCSUG 2010 Impact of model mis-specification on conditional power in interim survival analysis Chao L. Chen source 9
WUSS 2010 Planned Contrasts and Post Hoc Tests in MANOVA Made Easy Chii-Dean Joey Lin source 8
PHUSE EU 2010 Statistical Graphics for Review and Reporting in Clinical Development Kerstin Pietzko,
Michael O'Connell		 source
poster source		 12
SESUG 2010 Sample Size Calculation to Evaluate Mediation Analysis Rajendra Kadel source 12
PharmaSUG 2010 Linear Mixed Models in Clinical Trials using PROC MIXED Danyang Bing,
Xiaomin He		 12
SGF 2010 A Nonparametric Method to Assess Treatment Effects for Unbalanced Designs Using SAS/IML Michael Cunningham source 12
SGF 2010 Analysis of Survival Data with Recurrent Events Using SAS Rena Jie Sun,
Daniel T. Cotton		 source 8
SESUG 2009 The Use of SAS in Meta-Analysis Ryan C. Butterfield source 13
PHUSE EU 2009 The role of the statistician in data monitoring committees Fritz Schindel source 28
WUSS 2009 Computing Hazard Ratios and Confidence Intervals for a Two-Factor Cox Model with Interaction Terms Marla J. Husnik,
Jing Wang		 source 10
PharmaSUG 2009 Adhoc Analysis of Site By Treatment Interaction Alan Davis 9
PharmaSUG 2009 Computing Hazard Ratios and Confidence Intervals for a Two-Factor Cox Model with Interaction Terms Jing Wang,
Fred Hutchinson Cancer		 10
PharmaSUG 2009 Generating Model Based Subgroup Analysis Using SAS Procedures Tracy Lin,
Jie Huang		 4
PharmaSUG 2009 Modeling the Treatment Effect on a Median of a Percent Change from Baseline in a Log-normal Variable Using SAS PROC NLMIXED Aiming Yang 5
SGF 2009 %QLS SAS Macro: A SAS Macro for Analysis of Longitudinal Data Using Quasi-Least Squares Hanjoo Kim,
Justine Shults		 source 12
SGF 2009 Bayesian Modeling Using the MCMC Procedure Fang K. Chen source 22
WUSS 2008 Using Propensity Scores To Adjust For Treatment Selection Bias R. Scott Leslie source 7
SESUG 2008 Calculating the point estimate and confidence interval of Hodges-Lehmann's median using SAS software Lingling Han source 7
PHUSE EU 2008 Missing Data in Cross-Over Trials Edyta Mrowka source 7
PHUSE EU 2008 Statistically guided review of safety data in clinical trials Michael O'Connell,
Harry Southworth		 source 12
PharmaSUG 2008 Approximate Simultaneous Nonparametric Confidence Intervals for All Pair-Wise Comparisons and Comparisons with a Designated (Control) Group in a One-Way Layout Using the SAS System Paul Juneau,
Aditya Sikka,
Jiawei Qiao,
Michelle Gayari		 19
PharmaSUG 2008 Sample Size Estimation for (Bio)equivalence Testing Between Two Treatments Madan G. Kundu 13
PharmaSUG 2008 The Use of Propensity Scores and Instrumental Variable Methods to Adjust For Treatment Selection Bias R. Scott Leslie 8
SGF 2008 The Use of Propensity Scores and Instrumental Variable Methods to Adjust For Treatment Selection Bias R. Scott Leslie,
Hassan Ghomrawi		 source 8
NESUG 2007 A SAS Macro to Automate the Process of Pooling Sites Changhong Shi,
Lili Chen		 6
NESUG 2007 Common Pitfalls in SAS Statistical Analysis Macros in a Mass Production Environment Huei-Ling Chen,
Aiming Yang		 9
SESUG 2007 A SAS Macro to Automate the Process of Pooling Sites Changhong Shi source 6
SESUG 2007 Application of an Exact Covariate Matching Macro in Outcome Analysis Guiping Yang source 19
SESUG 2007 Selection Bias Adjustment: Root Canal Therapy and Self-reported Oral Health Mark S. Litaker,
Sandre F. McNeal,
Gregg H. Gilbert		 source 9
MWSUG 2007 RANDOM and REPEATED statements - How to Use Them to Model the Covariance Structure in Proc Mixed Charlie Liu 11
WUSS 2007 The Use of Propensity Scores and Instrumental Variable Methods to Adjust For Treatment Selection Bias R. Scott Leslie source 8
PHUSE EU 2007 A gentle introduction to Meta-analysis Angelo Tinazzi,
Jayne Tierney		 source 8
SCSUG 2007 Propensity Scoring Tutorial by Simulation in SAS Dee H. Wu,
David M. Thompson,
David Bard		 11
PharmaSUG 2007 A Review of Propensity Score Application in Healthcare Outcome and Epidemiology Guiping Yang 24
PharmaSUG 2007 Implementing Worst Rank Imputation Using SAS Qian Wang,
Eric Qi		 10
PharmaSUG 2007 Untied Worst-Rank Score Analysis William F. McCarthy 7
SGF 2007 Introducing a SAS Macro for Doubly Robust Estimation Michele Westreich,
Daniel Davidian,
Marie Wiesen,
Chris Jonsson Funk		 source 8
PNWSUG 2006 You Can't Stop Statistics: SAS/STAT Software Keeps Rolling Along Maura E. Stokes,
Robert N. Rodriguez		 32
PHUSE EU 2006 (Sample) Size DOES Matter John Salter source 10
PHUSE EU 2006 Analysis of incomplete two-period crossover trials with SAS PROC MIXED Jochen Müller-Cohrs source 8
PHUSE EU 2006 Statistical Graphics and Reporting in Drug Development Michael O'Connell,
Sven Knudsen		 source 13
SESUG 2006 PO04 PUB_BIAS: A SAS Macro for Detecting Publication Bias,
Gianna Rendina-Gobioff,
Jeffrey D. Kromrey		 source 17
NESUG 2006 Matching with Propensity Scores to Reduce Bias in Observational Studies Marcelo Coca-Perraillon,
Nan Liu		 10
NESUG 2006 You Can't Stop Statistics Maura E. Stokes,
Robert N. Rodriguez		 32
PharmaSUG 2006 A Method/Macro Based on Propensity Score and Mahalanobis Distance to Reduce Bias in Treatment Comparison in Observational Study Wuwei Wayne Feng,
Yu Jun,
Rong Xu		 11
PharmaSUG 2006 Estimate Carryover Effect in Clinical Trial Crossover Designs David Shen,
Zaizai Lu		 7
SUGI 2006 %hlmdata and %hlmrmpower: Traditional Repeated Measures vs. HLM for Multilevel Longitudinal Data Analysis?Power and Type I Error Rate Comparison Hua Fang source 11
SUGI 2006 Fixed Effects Regression Methods in SAS Paul D. Allison source 20
SUGI 2006 Using the RAND Function in SAS for Data Simulation in Clinical Trials Wenping Zhang source 7
SUGI 2006 You Can't Stop Statistics Maura E. Stokes,
Robert N. Rodriguez		 source 32
WUSS 2005 Revisiting the Cross-Over: A Two-Period Design Using a Treatment and a Placebo Qian Zhang,
Mable Kong		 source 10
PharmaSUG 2005 Power Analysis and Sample Size Estimation using Bootstrap Xiaomei Peng,
Guangbin Peng,
Celedon Gonzales		 7
SESUG 2004 A Simulation Study to Evaluate ANOVA and GEE for Comparing Correlated Proportions with Missing Values Mark S. Litaker source 6
SESUG 2004 Crossover Designs and Proc Mixed In SAS Hossein N. Yarandi source 11
MWSUG 2004 Calculation and Assessment of Inferential Test Statistics for Meta Analysis of Cross-Over Clinical Trials Hurley 8
MWSUG 2004 Using SAS Enterprise Guide to Automate and Customize Statistical Analyses for Pharmaceutical Data Alex Dmitrienko,
Cindy Lee		 6
PharmaSUG 2004 Automate Pharmacodynamic Analyses of Repeated Measure in Clinical Trials Using SAS Mixed Procedure Adeline Yeo,
Grace Li		 5
PharmaSUG 2004 Generating Least Square Means, Standard Error, Observed Mean, Standard Deviation and Confidence Intervals for Treatment Differences using Proc Mixed Richann J. Watson 12
PharmaSUG 2004 SAS Application in 2x2 Crossover Clinical Trial Wuwei Wayne Feng 10
PharmaSUG 2004 The Paired T-Test: Does PROC MIXED Produce the Same Results as PROC TTEST? Jack S. Nyberg 5
VIEWS 2003 Analysing Binary Outcome Data from a Crossover Design Study using the SAS System Anna Pictor presentation 8
PharmaSUG 2003 Confidence Intervals in Analysis and Reporting of Clinical Trials Guangbin Peng 8
SUGI 2003 Estimating Standard Errors for CLASS Variables in Generalized Linear Models Using PROC IML David J. Pasta,
Miriam G. Cisternas		 source 6
SESUG 2002 Comparison of Correlated Proportions using SAS PROC GLM: a Simulation Study Mark S. Litaker,
Daron G. Ferris		 source 4
WUSS 2002 A Macro for Constructing Confidence Intervals of Simple Difference in Dichotomous Data with Repeated Measurements Chii-Dean Joey Lin,
Kung-Jong Lui		 source 4
SUGI 2001 Analysis of Count Data Using SAS Alexander Pedan source 6
NESUG 2000 Methods for the Analysis of Clustered Ordinal Response Data Robert J. Gallop,
J. Richard Landis,
Thomas R. Ten Have		 7
SEUGI 2000 Skaen but not stirred - Why I like NLMIXED [presentation] Tim Auton source 38
PharmaSUG 2000 An Alternative to the Odds Ratio: A Method for Comparing Adjusted Treatment Group Effects on a Dichotomous Outcome P. Chris Holland 5
PharmaSUG 2000 Calculating a Nonparametric Estimate and Confidence Interval Using SAS Software Chris Decker 3
PharmaSUG 2000 Meta-Analysis with Linear and Nonlinear Multilevel Models Using PROC MIXED and PROC NLMIXED Eugene Komaroff,
Russell D. Wolfinger		 4
SUGI 2000 Custom Design of Complicated Block Experiments G. Bruce Schaalje,
Chris H. Bodily,
Bruce J. Collings		 source 4
SUGI 2000 Mixed-Up Mixed Models: Things That Look Like They Should Work But Don't, and Things That Look Like They Shouldn't Work But Do Robert M. Hamer,
Pippa M. Simpson		 source 8
SUGI 2000 Using Propensity Scores to Adjust for Group Differences: Examples Comparing Alternative Surgical Methods David J. Pasta source 7
SUGI 1999 A SAS Module/Macro Program for Computing Statistical Power Curves for Detecting Treatment Effect David Olaleye source 6
SUGI 1999 Cross Crossover Studies Off Your List Pippa M. Simpson,
Robert M. Hamer,
Shelly Y. Lensing		 source 7
WUSS 1998 Estimating Standard Errors of Treatment Effects for Probit Models and for Linear Models of Log-Transformed Variables with PROC IML David J. Pasta,
Miriam Cisternas,
Cynthia L. Williamson		 source 6
SESUG 1998 Multiple Comparison Procedures with SAS Chung-Kuei Chang 9
SEUGI 1998 SCHARP: Survival Curve and Hazard Ratio Program Angelo Tinazzi,
Jayne Tierney,
Lesley Stewart,
Max Parmar,
Valter Torri		 source 9
SEUGI 1998 Unpleasant data? A chance of powerful multi-variant analysis in clinical trials with data not meeting the conditions Thomas Bregenzer source 13
WUSS 1997 The Sums of Squares Are All the Same - How Can the LSMEANS Be So Different? Lori Potter,
David J. Pasta		 source 6
NESUG 1997 Survival Analysis: Non-Traditional Applications for Non-Statisticians Margaret Ann Goetz 5
SUGI 1997 Graphical and Analytical Tools for the Analysis of Two-Period Crossover Clinical Trials Jeff A. Sloan,
Paul J. Novotny,
Charles L. Loprinzi,
Suresh Nair		 source
SCSUG 1996 Who Says Study Effect Doesn't Matter? O. M. Little 11
SEUGI 1996 A SAS/AF software application for sample size and power determination Fiona Portwood source 8
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 A SAS Program for the Assessment of Unbalanced Data in Two- Sequence, Three-Period CrossoverTrials Annpey Pong,
Shein-Chung Chow		 source 6
NESUG 1995 Implementing a Modified Method of Weighted/Unweighted Means Robert H. Brown 9
NESUG 1995 More on PROC PHREG: Conditional Logistic Regression (or Should We Do Another Study..?) Peter P. Gaccione 10
NESUG 1995 When Chi-Square Does Not Hold: How to Analyze Tables With Low Cell Frequencies With SAS Lothar Tremmel 9
SEUGI 1995 SAS Macros for Nonparametric Tests in the Case of Multivariate Incomplete Data from two Populations Thomas Bregenzer source 7
WUSS 1994 A SAS MACRO for the Ricardian Model of International Trade Zaki Eusufzai source 17
WUSS 1994 An Effective Method to Construct Coefficients in CONTRAST and ESTIMATE Statements Used in ANOVA George C. J. Fernandez source 17
NESUG 1994 Statistical Methods for Assessing the Safety of Products Evaluated in Human Clinical Trials John Sourby 8
SEUGI 1994 SAS System Macros for Multi-variate Two-sample Tests in the Case of Incomplete Data Thomas Bregenzer source 10
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 Modification of Two-Stage Least Squares in Quasi-Experiments Alex Ezuzides,
Raymond C. Peck		 source 9
MWSUG 1993 Statistical Graphs in Environmental Regulatory Studies Larry R. Holden 8
SEUGI 1993 SAS Macros for Comparisons with Multiple Endpoints Thomas Bregenzer source 7
SEUGI 1993 The Analysis of Repeated Measures Designs Using the SAS System Alun Bedding source 9
MWSUG 1992 A Monte Carlo Evaluation of the Rank Transformation for Cross-Over Trials George W. Pasdirtz 6
SUGI 1992 Using the GLM Procedure to Analyze Multivariate Response in Crossover Designs Julie Myers Grender,
William D. Johnson		 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
SUGI 1991 Analysis of 2 x 2 Cross-over Trials Using an Integrated Macro Package Harvie Chang,
Tamara R. Strang		 source 6
SUGI 1991 The Analysis of Two-Period Cross-Over Design with a Binary Response Variable S. Geethakrishnan source 4
SUGI 1990 Analyzing Balanced or Unbalanced Latin Squares and Other Repeated-Measures Designs for Carryover Effects Using the GLM Procedure D. A. Ratkowsky,
J. R. Alldredge,
J. W. Cotton		 source 6
SUGI 1990 The Analysis of Data from 2 X 2 Crossover Trials with Baseline Measurements Joe DiGennaro,
William C. Huster		 source 6
SEUGI 1989 A Bioassay Method Using SAS/STAT Software C. M Fenton,
P. Blood		 source 12
SEUGI 1989 Exact Distribution For 2-Sample-Permutation- And Ranktests Using The Streitberg-Röhmel-Algorithm And SAS/IML Software Heidi Voss 10
SUGI 1989 A SAS/IML Program for Randomization Analysis of Dose Response Curves Dean E. Nelson source 4
SUGI 1989 Multivariate Models for the Analysis of Crossover Experiments Vernon M. Chinchilli,
Ronald K. Elswick		 source 5
SEUGI 1988 SAS/IML Program to Analyse a Two-Period Crossover Trial P.J.B. Berry source 10
SUGI 1988 Logit Models for Ordered Categorical Response Data Alan Agresti source 9
SUGI 1988 The Analysis of Complete Blocks Using Methods Based on Ranks Ronald L. Iman source 9
SUGI 1988 To Pool or Not to Pool in a Multicenter Clinical Trial Gregory T. Schwemer source 4
SUGI 1986 PROC RSMCB: A Procedure for Ranking, Selection, and Multiple Comparisons with the Best James C. Aubuchon,
Shanti S. Gupta,
Jason C. Hsu		 source 5
SUGI 1985 An Interactive, Menu-Driven SAS System for Sample Size and Power Computations in Clinical Trial Design Gregory G. Enas,
Walter W. Offen,
John D. Taulbee		 source 6
SUGI 1983 Overview of Categorical Data Analysis Methods Ingrid A. Amara,
Susan Atkinson,
Gary G. Koch,
William M. Stanish		 source 10
SUGI 1982 The Evaluation of Federal Programs in Education Garrett K. Mandeville source
SUGI 1981 Analysis of a Two-Period Crossover Design Using Macro XSOVER Irving K. Hwang source
SUGI 1979 Analysis of Covariance of Incomplete Data in Experiments with Repeated Measurements in Clinical Trials Harji I. Patel source 5
SUGI 1979 Using U-Model Techniques to Test Hypotheses in the Linear Model Emilio A. Icaza,
Kenneth L. Koonce		 source 5
SUGI 1977 Some Graphical and Statistical Descriptions of Interactions Paul N. Hinz source 5
SUGI.ONE 1976 Use of the Harvey Procedure Walter R. Harvey source 3

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