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power analysis

108 papers and 1 presentation; 105 titles.

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Conference × Year × Title × Authors Extras Pages
PharmaSUG 2026 A Faster Algorithm for the Finkelstein-Schoenfeld Test and Win Ratio in Hierarchical Composite Endpoint Analysis James Austrow source 13
PharmaSUG 2026 Implementation of Quality Tolerance Limits in Statistical Programming Yang Gao source 4
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 Critical & Sensitive Information (CSI) Paper AS02 Revolutionizing Clinical Quality: A Frontier Approach with Quality by Design (QbD), Infrastructure Modernization and Data-Driven Analytics Priti Gupta,
Deepa Balaji		 source
presentation source		 12
PHUSE APAC 2026 Innovative Strategies for Managing Missing Data in Real-World Data: Insights from APAC Global Capability Centers Likhita Kolli,
Tuhin James Paul		 source
poster source		 12
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 Navigating Experimental Arms in Subtype Studies: Strategies for Precision and Clarity Narek Torosyan,
Edgar Sargsyan		 source
presentation source		 4
SESUG 2025 Introduction to Data Simulation Jason Brinkley 10
PharmaSUG 2025 Simulating Optimal Sample Sizes for Canine Jaws Using SAS Chary Akmyradov,
Lida Gharibvand		 source 11
PHUSE EU 2024 Artificial Intelligence Potential Use Cases in Clinical Data Engineering Deepak Pakalapati,
Mounika Pillamarapu		 source
presentation source		 8
WUSS 2024 Simulating Optimal Sample Sizes for Joyful Canine Jaws Using SAS Chary Akmyradov,
Lida Gharibvand		 source 11
WUSS 2024 The Current State of Teaching Biostatistics in Academia [presentation] Lida Gharibvand source 14
PHUSE US 2024 InnoRand - Innovative Randomisation Yinfei Wu,
Ivo Marek		 source
presentation source		 4
PHUSE US 2024 SAS PROC MI: Your Impeccable Tool for Enhanced Data Analysis Through the Lens of Multiple Imputation Anush Kurghinyan,
Shahrzad Talebian		 source
presentation source		 7
SESUG 2023 How to use SAS POWER procedure to plan a study Xiaofeng (Steven) Liu source 4
SGF 2020 Sample Size Calculations Using SAS, R, and nQuery Software Jenna Cody source 19
SGF 2020 Simulating Data for Complex Linear Models Phil Gibbs,
Kathleen Kiernan		 source 20
SGF 2020 Surviving the Cox Proportional Hazards Model with the POWER Procedure Rachel R. Baxter source 6
WUSS 2019 Statistical Power Calculations Using SAS Software Russell M. Lavery source 18
PharmaSUG 2019 Statistical Assurance in SAS: An Introduction and User-s Guide Jonathan L Moscovici,
Milena Kurtinecz		 source 8
SESUG 2018 Introduction to Data Simulation Jason Brinkley source 9
SGF 2018 Power Analysis for Generalized Linear Models Using the New CUSTOM Statement in PROC POWER John M. Castelloe source 17
SGF 2018 SAS Macros for Computing Causal Mediated Effects in Two- and Three-Wave Longitudinal Models David P. MacKinnon,
Matthew Valente		 source 18
SGF 2017 SAS Macros for Computing the Mediated Effect in the Pretest-Posttest Control Group Design David P. MacKinnon source 10
SESUG 2016 Introduction to Data Simulation Jason Brinkley source 8
WUSS 2016 Knowledge is Power: The Basics of SAS Proc Power Elaina Gates source 5
SGF 2016 PROC GLIMMIX as a Teaching and Planning Tool for Experiment Design Walter W. Stroup source
zip		 19
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
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
SESUG 2014 ANOVA_HOV: A SAS Macro for Testing Homogeneity of Variance in One-Factor ANOVA Models Diep T. Nguyen,
Thanh V. Pham,
Patricia Rodríguez de Gil,
Tyler Hicks,
Yan Wang,
Isaac Y. Li,
Aarti P. Bellara,
Jeanine L. Romano,
Eun Sook Kim,
Harold Holmes,
Yi-Hsin Chen,
Jeffrey D. Kromrey		 source 12
SESUG 2014 Overview of Analysis of Covariance (ANCOVA) Using GLM in SAS Abbas S. Tavakoli source 10
SESUG 2014 Strimmed_t: A SAS Macro for the Symmetric Trimmed t Test Diep T. Nguyen,
Anh P. Kellermann,
Eun Sook Kim		 source 12
PHUSE EU 2014 Small Sample Bayesian Factor Analysis Dirk Heerweghm source
presentation source		 18
SGF 2014 Power and Sample Size for MANOVA and Repeated Measures with the GLMPOWER Procedure John M. Castelloe source 20
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
SESUG 2013 Introducing the New ADAPTIVEREG Procedure for Adaptive Regression Warren F,
Weijie Cai		 source 21
PharmaSUG 2013 Combining Analysis Results from Multiply Imputed Categorical Data Bohdana Ratitch,
Ilya Lipkovich,
Michael O'Kelly		 source 19
SGF 2013 Variance Heterogeneity and Non-Normality: How the SAS TTEST Procedure Can Keep Us Honest Aarti P. Bellara,
Anh P. Kellermann,
Diep T. Nguyen,
Eun Sook Kim,
Jeffrey D. Kromrey,
Patricia Rodríguez de Gil,
Yi-Hsin Chen		 source
pdf		 10
SESUG 2012 PROC TTEST (Old Friend), What Are You Trying to Tell Us? Diep T. Nguyen source 12
SESUG 2012 Random Effects Simulation for Sample Size Calculations Using SAS Random Effects Simulation source 11
WUSS 2012 Modular processing for Prep-to-research anaylsis - interfacing XML SAS and Microsoft Excel David Tabano source 16
WUSS 2012 Sample Size Calculation and Power Analysis for Design of Experiments Using Proc Glmpower Chii Dean source 10
SGF 2012 A Simple Way to Program Power Calculations Robert Lew,
Hongsheng Wu		 source 16
SCSUG 2011 A Simulation Study for Power Analysis in a Longitudinal Study Using SAS Ravi Lingineni source 4
MWSUG 2011 A Macro to Estimate Sample-size Using the Non-Centrality Parameter of a Non-Central F-Distribution Matthew C. Fenchel,
Raouf S. Amin,
Rhonda D. VanDyke		 20
MWSUG 2011 Bootstrap power analysis using SAS Douglas Thompson,
Nort Holschuh,
Bruce Barton,
Ann Albertson		 8
SGF 2011 Living with Generalized Linear Mixed Models Walter W. Stroup source 18
PharmaSUG 2010 Using SAS Proc Power to Perform Model-based Power Analysis for Clinical Pharmacology Studies Peng Sun 11
SGF 2010 A Grad Student 'How-To' Paper on Grant Preparation: Preliminary Data, Power Analysis, and Presentation Elisa L. Priest,
Derek Blankenship		 source 14
SGF 2010 Clinical Trials Simulation: A Publicly Available, Grid-Enabled, GUI-Driven SAS System Peter H. Westfall,
Alex Dmitrienko,
Cynthia DeSouza,
Alin Tomoiaga		 source 13
SGF 2010 Dancing the Sample-Size Limbo with Mixed Models: How Low Can You Go? Bethany A. Bell,
Grant B. Morgan,
Jason A. Schoeneberger,
Brandon L. Loudermilk,
Jeffrey D. Kromrey,
John M. Ferron		 source 11
SGF 2009 Parsimony vs. Complexity: A Monte Carlo Investigation of Hierarchical and Cross-Classified Modeling Using SAS PROC MIXED Bethany A. Bell,
Corina M. Owens,
Jeffrey D. Kromrey,
John M. Ferron		 source 12
SESUG 2008 A SAS Macro for Statistical Power Calculations in Meta-Analysis Guy Cafri source 8
PHUSE EU 2008 Evaluation of Diagnostic Agents: a SAS Macro for Sample Size Estimation Using Exact Methods Stefano Vezzoli source 8
MWSUG 2008 A Multivariate Ranking Procedure to Assess Treatment Effects Alan Y Chiang,
Grace Li,
Ying Ding,
Ming-Dauh Wang		 7
PharmaSUG 2008 Sample Size Estimation Through Simulation of a Random Coefficient Model by Using SAS Junliang Chen,
Shannon Stock,
Chunqin Deng		 8
SGF 2008 Updates to SAS Power and Sample Size Software in SAS 9.2 Wayne E. Watson source 10
PNWSUG 2007 An Introduction to Statistical Power Calculations for Linear Models with SAS 9.1 Robin High 17
SGF 2007 GLMM_SIM: A SAS Macro for Evaluating the Statistical Integrity of General Linear Mixed Models James T. Hess,
Melinda R. Hines,
Constance Kromrey,
Jeffrey D. Lee,
Reginald S. Luther,
Stephen L. Coraggio		 source 10
SESUG 2006 MLM_SIM: A SAS Macro for the Statistical Investigation of Mixed Models Jeffrey D. Kromrey source 15
PharmaSUG 2006 Randomization in Clinical Trial Studies David Shen,
Zaizai Lu		 8
PharmaSUG 2005 Power Analysis and Sample Size Estimation using Bootstrap Xiaomei Peng,
Guangbin Peng,
Celedon Gonzales		 7
SUGI 2004 Sample-Size Analysis in Study Planning: Concepts and Issues, with Examples Using PROCs POWER and GLMPOWER Ralph G. O'Brien,
John M. Castelloe		 source 12
SESUG 2003 EFFECT_CI: A SAS Macro for Constructing Confidence Intervals Around Standardized Mean Differences Around Standardized Mean Differences source 6
PharmaSUG 2003 Using SAS to Evaluate Integrals and Reverse Functions in Power and Sample Size Calculations Xingshu Zhu,
Shuping Zhang		 6
SESUG 2002 FDR_TEST: A SAS Macro for Calculating New Methods of Error Control in Multiple Hypothesis Testing Jeffrey D. Kromrey,
Kristine Y. Hogarty		 source 6
PharmaSUG 2002 Fast Two-Sample Permutation Tests, Even When One Sample is Large, that Efficiently Maximize Power Under Crude Monte Carlo Sampling John D. Opdyke 10
NESUG 2001 Optimizing Survey Research from Start to Finish Using SAS Software Lark Lee,
Yvonne Brandreth		 7
NESUG 2001 Power and Sample Size Determination for Linear Models John M. Castelloe 13
WUSS 2001 Using SAS Functions for Power Analysis and Sample Size Estimation Mel Widawski source 5
SESUG 2001 Power and Sample Size Determination for Linear Models John M. Castelloe source 13
SESUG 2001 Using the SAS System to Study the Gender and Level Measurement Equivalence of a Multi-rater Survey Multi-rater Survey source 6
SCSUG 2001 Power and Sample Size Determination for Linear Models John M. Castelloe,
Ralph G. O'Brien		 13
SCSUG 2001 Using the SAS System to Demonstrate the Equivalence of On-line and On-Papeer Survey Adminstration across Levels of Raters Jim Penny 5
PharmaSUG 2001 Power and Sample Size Determination for Linear Models John M. Castelloe 14
SUGI 2001 Power and Sample Size Determination for Linear Models John M. Castelloe,
Ralph G. O'Brien		 source 13
SUGI 2001 Probabilistic Hindsight: A SAS Macro for Retrospective Statistical Power Analysis Kristine Y. Hogarty,
Jeffrey D. Kromrey		 source 10
SCSUG 2000 Multi-Level Intervention Study Data and PROC MIXED Tom Bohman 13
SESUG 2000 Emerging Technologies Roadmap A Decision Tree Guide to Understanding SAS Strengths Gregory S. Barnes Nelson source 9
SUGI 2000 Design and Analysis of Cancer Control Studies via the SAS System Jeff A. Sloan,
Charles L. Loprinzi,
Paul J. Novotny		 source 10
SUGI 2000 Sample Size Computations and Power Analysis with the SAS System John M. Castelloe source 8
MWSUG 1999 Sample Size Determination From A Pilot Bioequivalence Study For A Future Pivotal Bioequivalence Study: A SAS Procedure Xiang Gao,
Henry Cheng		 7
SUGI 1999 A SAS Module/Macro Program for Computing Statistical Power Curves for Detecting Treatment Effect David Olaleye source 6
MWSUG 1998 A Tour of UnifyPow: A SAS Module/Macro for Sample-Size Analysis Ralph G. O'Brien 11
PharmaSUG 1998 A SAS/Frames Application to Estimate Sample Size and Power for Clinical Trials Brian Mitchell 4
PharmaSUG 1998 Use of Pilot Trials as Screening Procedure in Generic Drug Product Development: Statistical Power and Influential Factors Yibin Wang 5
SUGI 1998 A Tour of UnifyPow: A SAS Module/Macro for Sample-Size Analysis Ralph G. O'Brien source 10
SUGI 1998 Application of Maximum Contrast Method to Biomedical Data Using MU L TTEST Chikuma Hamada,
Junji Kishimoto		 source 6
SUGI 1997 UnifyPow: A SAS Macro for Sample-Size Analysis Ralph G. O'Brien source 6
SUGI 1996 Determining the Expected Mean Squares and Subsequent Power Calculations: An Application to Biostatistics Jon M. Lindenauer,
Eric C. Burdge,
John W. Philpot		 source 5
SUGI 1993 A Simulation-Based Project For Experimental Design Based on SAS Software Michael Friendly source 8
SESUG 1993 New SAS Modules for Practical Power Analysis Dan Bowling,
Ralph G. O'Brien		 9
SUGI 1992 POWER: A Simple Macro for Power and Sample Size Calculations Kristin Latour source 5
SCSUG 1991 Calculating the Power Function of the Wilcoxon Rank Sum Test in 2xK Tables Mark Von Tress 7
SEUGI 1991 Pharmacokinetic Analysis with the SAS System Martin F. Michael source 10
SUGI 1991 A Procedure for Deciding Which Treatments to Accept in a Screening Study Involving Pseudo-Bernoulli Data Ralph A. DeMasi,
Dana Quade		 source 7
SUGI 1991 Power Analysis and Instructional Monte Carlo Simulations Richard W. Cole source 4
SUGI 1990 Using a SAS/AF Application to Calculate the Power of a Statistical Test John F. Schneider,
Robert A. McLean,
William L. Sanders		 source 6
SUGI 1988 Power Analysis in an Enhanced GLM Procedure: What It Might Look Like Ralph G. O'Brien,
S. Paul Wright		 source 6
SUGI 1986 Power Analysis for Linear Models Ralph G. O'Brien source 8
SUGI 1986 Using the SAS System to Perform Power Analyses for Log-Linear Models Ralph G. O'Brien source 7
SUGI 1985 Macro Power: A Procedure to Generate Wilcox on Rank Sum Power Curves Michael J. Todd source 4
SUGI 1984 Estimating Power for Tests of the Multivariate General Linear Hypothesis Keith E. Muller,
Bercedis L. Peterson		 source 5
SUGI 1984 Power Analysis for Linear Models: The Time Has Come Virginia I. Lohr,
Ralph G. O'Brien		 source 7
SUGI 1984 Power Analysis for Multivariate Linear Models: New Results and SAS Software Make It Practical Keith E. Muller,
Bercedis L. Peterson		 source 6
SUGI 1984 Power Analysis for Univariate Linear Models: The SAS System Makes It Easy.. Virginia I. Lohr,
Ralph G. O'Brien		 source 6
SUGI 1983 Effect Size and Power in Two Factor Nonorthogonal ANOVA: A Monte Carlo Investigation Margaret J. Martin,
William A. Powers		 source

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