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211 papers and 18 presentations; 219 titles.

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Conference × Year × Title × Authors Extras Pages
PharmaSUG CN 2026 An Integrated, AI-Augmented R Shiny Platform for Oncology Clinical Trial Decision Intelligence: From CDISC Data to Go/No-Go in One Unified Hub Zhiping Yan source 28
PharmaSUG 2026 Stop Guessing. Start Matching. High-Impact SAS PRX Patterns in 20 minutes Charu Shankar source 7
PHUSE US 2026 Across the Multiverse ... Statistically Speaking Cralen Davis source
presentation source		 4
PHUSE US 2026 Is There Really Any Benefit to Stratified Randomisation in Practice? Pavankumar Bhagat source
presentation source		 9
PHUSE US 2026 Performance-Driven Risk Oversight for AI Agents in Clinical Research Laxmiraju Kandikatla source
presentation source		 10
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 EU 2025 Collaborative Industry Open-Source Solutions for Clinical Trial Quality Management Björn Koneswarakantha,
Frederik Collin		 source
presentation source		 9
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 New Multiple Imputation Approaches with SAS Andrea Parodi source
presentation source		 2
PHUSE EU 2025 Statistical Endpoints and Analysis in Diagnostic Imaging: The Matrix Has You and Your Data Srinivas Lanka,
James Sykes		 source
presentation source		 17
SESUG 2025 Five Easy Ways to Make Your SAS Code Run Faster Mark L. Jordan 18
SESUG 2025 Fuzzy Matching with SAS PROC SQL Mark L. Jordan 16
PharmaSUG 2025 Promising Zone Designs for Sample Size Re-estimation in Clinical Trials: Graphical Approaches Using SAS Zhao Yang,
Shivani Nanda		 source 18
PHUSE US 2025 Dismantling the Black Box: Why We Need to Think Bigger About AI Integration Christina Dinger,
Joe Lebers		 source
presentation source		 7
MWSUG 2024 A General Review of Fuzzy Matching Techniques and Their Capabilities Using SAS Kirk Paul Lafler source 31
WUSS 2024 Simulation in SAS for Estimating Power [presentation] Michael Williams source 18
PharmaSUG CN 2024 Roche automated esub translation Joe Zhu,
Xiaoli Duan,
Siye Liu		 source 3
PharmaSUG 2024 Generative Artificial Intelligence in sample size estimation - challenges, pitfalls, and conclusions Igor Goldfarb,
Vikas Sharma		 source 26
PharmaSUG 2024 Versatile and efficient graphical multiple comparison procedures with {graphicalMCP} Ethan Brockmann source 3
PHUSE US 2024 Beyond Outliers: Unsupervised Anomaly Detection in Clinical Trial Data Helena Yaben,
Kian Norouzi		 source
presentation source		 9
PHUSE US 2024 Comparison of Standard Log-Rank Test with Selected Alternatives Elena Valkanova,
Bulat Fatykhov		 source
poster source		 18
PHUSE EU 2023 Inference on Weighted Subjects: Comparing Weighted Individual Patient Data with Results from the Literature [poster] Andrea Parodi,
Dimitri Petratchenko		 source 1
PHUSE EU 2023 Road to Rome or Roaming - A Reprise [presentation] Francis Kendall,
Christian Mueller		 source 32
WUSS 2023 Introduction to Machine Learning - Descriptions and Best Practices Jim Box source 13
PharmaSUG 2023 Industry metrics for standards utilization and validation rules Sergiy Sirichenko source 13
PharmaSUG 2023 What is Machine Learning, anyway? Jim Box source 11
PHUSE US 2023 Handling Multiple Adaptations in One Clinical Trial Parvee Kumar,
Shrutimita Pokhariyal		 source
presentation source		 6
PHUSE US 2023 Reducing Rate of False Positives Risk Signals with Risk Management Strategy Vera Pomerantseva source
presentation source		 5
PHUSE US 2023 The Rule of Three: Applications in Leadership, Communication, and Strategy [presentation] Michael S Rimler source
video		 11
PHUSE EU 2022 Inference from weighted subjects Andrea Parodi source
poster source		 4
SESUG 2022 A Two-Staged Local Regression Based Binning Method for Weight of Evidence Transformation in Credit Scoring Models Hui Wang,
Shirong Huang,
Emma Zhou,
Erin Martin		 source 30
PharmaSUG 2022 An Expanded Set of SAS Macros for Calculating Confidence Limits and P-values Under Simon's Two-Stage Design Accounting for Actual and Planned Sample Sizes Mikhail Melikov,
Alex Karanevich		 source 8
PharmaSUG 2022 Analysis of sample size calculations in clinical trial - errors, pitfalls and conclusions Igor Goldfarb,
Ritu Karwal,
Xiaohua Shu		 source 14
PharmaSUG 2022 Explanations in the Study Data Reviewer's Guide: How's It Going? Kristin Kelly source 9
PHUSE US 2022 Explanations in the Study Data Reviewer's Guide: How's It Going? [presentation] Kristin Kelly source
video		 13
PHUSE EU 2021 Automated Testing of the Programming Workflow Using Cypress [presentation] Darwin Hadley source
video		 15
PHUSE EU 2021 Metadata: Errors Not Detected by the Pinnacle 21 Tool [presentation] Caroline Pelckmans,
Pamphile Beaujean		 source
video		 20
PHUSE US 2021 Central Statistical False Positives - Predicting True Signals with Machine Learning [presentation] Dorothea Ugi source
video		 24
SGF 2021 Automated Vehicle Odometer Reading Using SAS for AI and Computer Vision Tyler Rosacker,
Kedar Prabhudesai,
Hardi Desai,
Neela Vengateshwaran,
Varunraj Valsaraj		 source
pdf		 17
PHUSE EU 2020 Define-XML for ADaM: Clinical Standards Toolkit vs. Pinnacle 21? [presentation] Frederikke Høyer source
video		 16
PHUSE EU 2020 Getting It Right: Refinement of SEND Validation Rules [presentation] Kristin Kelly source
video		 29
SGF 2020 Bayesian Sequential Monitoring of Clinical Trials Using SAS Matthew A. Psioda source 13
SGF 2020 Deploying Machine Learning Models in an Anti-Money Laundering (AML) Program Beth Herron,
Saurabh Duggal		 source 11
SGF 2020 Sample Size Calculations Using SAS, R, and nQuery Software Jenna Cody source 19
SGF 2020 SAS DataFlux Matchcodes: A Practical Use at the Canada Revenue Agency for Tax Filing Status Jason A. Oliver source 12
SGF 2020 Testing Hypotheses for Equivalence and Non-inferiority with Binary and Survival Outcomes Joseph C. Gardiner source 23
SGF 2020 Using Analytics to Predict Tax Recovery and Prioritize Audits and Investigations in Canada Jason A. Oliver source 19
SGF 2020 Using SAS PRX functions for medical records Amy Alabaster,
Mary Anne Armstrong		 source 13
PharmaSUG 2020 Getting It Right: Refinement of SEND Validation Rules Kristin Kelly source 7
PHUSE US 2020 A Comparison of Machine Learning Algorithms for Binary Classification of Free-text Fields Using SAS, R, and Python Michael S Rimler source
presentation source		 12
PHUSE US 2020 Getting It Right: Refinement of SEND Validation Rules Kristin Kelly,
Blue Bell		 source
presentation source		 6
PHUSE US 2020 Interactive Real-world Data Analysis Using Machine Learning Algorithms James J. Kim source
poster source		 5
SCSUG 2019 Building a Neural Network Scoring Model with JMP and Microsoft SQL Server to predict Aggregate Motor Vehicle Driver Alcohol Impairment David Whitchurch source 10
MWSUG 2019 Evaluate your SCORE: Logistic regression prediction comparison using the SCORE statement Robert G. Downer 6
MWSUG 2019 Logistic Regression, Basics and Beyond Bruce S. Lund 35
MWSUG 2019 Sample Size and Design Considerations in Studies Assessing Non-Inferiority using Continuous Outcomes Michael G. Wilson 19
PharmaSUG 2019 Performing Analytics on Free-Text Data Fields: A Programer-s Wurst Nitemare Michael S Rimler,
Matt Pitlyk		 source 18
SGF 2019 Factors Influencing Academic Performance Onkar Mayekar,
Miriam McGaugh		 source 9
SGF 2019 Improve Your AML Monitoring While Reducing Costs with SAS Viya Calvin Crase,
Chris St. Jeor		 source 11
SGF 2019 Machine Learning for Effective Surveillance with SAS Adaptive Learning and Intelligent Agent System Rory MacKenzie source 14
PHUSE US 2019 Quantifying Dynamic Risk with Predictive Analytics Susan Olson,
Connor English		 source
presentation source		 7
PHUSE US 2019 Seven Habits of Highly Effective (Validation Issue) Managers Amy Garrett source
presentation source		 6
PHUSE EU 2018 Implementing Advanced Analytics and Machine Learning in Risk-based Strategies Rajneesh Patil source
presentation source		 3
PHUSE EU 2018 Optimizing the Traceability Method in ADaM Parallel Conversions Roxane Debrus source
presentation source		 15
WUSS 2018 Interpreting electronic health data using SAS PRX functions Amy Alabaster,
Mary Anne Armstrong		 source 13
PHUSE US 2018 Planning and Executing a Two-Stage Adaptive Design with Interim Analysis [poster] Katy Jaffee source 1
SGF 2018 A Fraud Management Solution for Middle Market Banks and Ways to Reduce False Positives Gourish Hosangady source 6
SGF 2018 Evaluating the Accuracy of Clinical Prediction Models for Binary and Survival Outcomes Joseph C. Gardiner source 21
SGF 2018 Mitigating the Effects of Class Imbalance Using SMOTE and Tomek Link Undersampling in SAS Kyle Biron source 20
PHUSE EU 2017 Central Statistical Monitoring Tammy McIver source
presentation source		 7
PHUSE EU 2017 Futile or Not? An Interim Analysis Case Study Ingrid Franklin source
presentation source		 9
SGF 2017 Cold-Start Solution to A/B Testing Using Adaptive Sample Size Modification Bo Zhang,
Liwei Wang		 source 9
SGF 2017 Continuous Predictors in Regression Analyses Ruth Croxford source 12
SGF 2017 Exploring the Art and Science of SAS Text Analytics: Best Practices in Developing Rule-Based Models Murali Krishna Pagolu,
Cheyanne Baird,
Christina Engelhardt		 source 15
SGF 2017 Predictive Accuracy: A Misleading Performance Measure for Highly Imbalanced Data Josephine Akosa source 12
SGF 2017 Timing is Everything: Detecting Important Behavior Triggers Daymond Ling source 12
SGF 2017 Using SAS to Estimate SE, SP, PPV, NPV, and Other Statistics of Chemical Mass Casualty Triage Abbas S. Tavakoli,
Joan Culley,
Jane Richter,
Sara Donevant,
Jean Craig		 source
pdf		 11
SESUG 2016 In the Pursuit of Balanced Groups: A SAS Macro for an Adaptive Randomization Test Tyler Hicks,
Jeffrey D. Kromrey		 source 9
SESUG 2016 Mixture Priors 101: Using SAS to Obtain Powerful Frequentist Inferences with Bayesian Methods Tyler Hicks,
Jeffrey D. Kromrey		 source 8
PHUSE EU 2016 Multiplicity Issues in Clinical Trials - Look at it with a Magnifying Glass! Madhusudhan Bandi source
presentation source		 6
MWSUG 2016 An Animated Guide: Insights into the Logic of the ROC Curve Russell M. Lavery 8
MWSUG 2016 Frequentist and Bayesian Interim Analysis in Clinical Trials: Group Sequential Testing and Posterior Predictive Probability Monitoring Using SAS Kechen Zhao 14
WUSS 2016 An Animated Guide: Insights into the Logic of the ROC Curve Russell M. Lavery source 8
PharmaSUG 2016 ROC Curve: Making way for correct diagnosis Manoj Pandey,
Abhinav Jain		 source 12
SGF 2016 Alerts Don't Launder Money (and Finance Terrorism)--People Do! Kathy Hart source 7
SGF 2016 Making Better Decisions about Risk Classification Using Decision Trees in SAS Visual Analytics Stephen M. Overton,
Ben Murphy		 source 13
SGF 2016 Money Launderers Beware! Catching You Is Just a Point-and-Click Away Renee Palmer,
Yue Chai		 source 14
MWSUG 2015 Intuitive Demonstration of Statistics through Data Visualization of Pseudo-Randomly Generated Numbers in R and SAS Jack Sawilowsky 11
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
SESUG 2015 ANOVA_Robust: A SAS Macro for Various Robust Approaches to Testing Mean Differences in One-Factor ANOVA Models Thanh V. Pham,
Eun Sook Kim,
Diep T. Nguyen,
Yan Wang,
Jeffrey D. Kromrey,
Yi-Hsin Chen		 source 14
SESUG 2015 Tips for Identifying Patient Characteristics Associated with Diagnostic Concordance between Two Measures Using SAS Seungyoung Hwang,
Johns Hopkins		 source 5
WUSS 2015 Sample Size Convergence of Denominator Degrees of Freedom Method Options in SAS PROC MIXED Timothy Banh source 13
PharmaSUG 2015 Missing Data For Repeated Measures: Single Imputation VS Multiple Imputation Giulia Tonini,
Simona Scartoni,
Camilla Paoli,
Andrea Nizzardo,
Angela Capriati		 source 10
PharmaSUG 2015 Simple Tests of Hypotheses for the Non-statistician: What They Are and Why They Can Go Bad Arthur L. Carpenter source 9
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 Entity Resolution and Master Data Life Cycle Management in the Era of Big Data John Talburt source 16
SGF 2015 Using SAS/STAT Software to Implement a Multivariate Aadaptive Outlier Detection Approach to Distinguish Outliers from Extreme Values Paulo Macedo source 12
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 Strimmed_t: A SAS Macro for the Symmetric Trimmed t Test Diep T. Nguyen,
Anh P. Kellermann,
Eun Sook Kim		 source 12
SESUG 2014 Using SAS/STAT to implement a multivariate adaptive outlier detection approach to distinguish outliers from extreme values Paulo Macedo source 11
PHUSE EU 2014 Data Challenges in Adaptive Trials Claudio Garutti source
presentation source		 5
PHUSE EU 2014 PROC EASTMONITOR - A SAS Add-on for Monitoring Adaptive Clinical Trials Sheetal Solanki,
Ajay Sathe		 source
presentation source		 15
PharmaSUG 2014 Let SAS Improve Your CDISC Data Quality Wayne (Weizhen) Zhong source 12
PharmaSUG 2014 OpenCDISC Validator Implementation: A Complex Multiple Stakeholder Process Terek J. Peterson,
Gareth Adams		 source 9
SGF 2014 Analysis of Data with Overdispersion Using SAS [presentation] Jorge Morel source 67
SGF 2014 The Commonly Used Statistical Methods to Control The Probability of an Overall Type I Error and the Application in Clinical Trial Lixiang Yao source 7
SGF 2014 The Use of Analytics for Insurance Claim Fraud Detection: A Unique Challenge Roosevelt Mosley,
Nick Kucera		 source 15
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
WUSS 2013 An Algorithm for ARIMA Dynamic Regression Variable Selection Ross Bettinger source 14
SCSUG 2013 The Complexities of an Address Barry E. Mullins source 7
SESUG 2013 Area under a Receiving Operating Characteristic (ROC) Curve: comparing parametric estimation, Monte Carlo simulation and numerical integration Receiver Operating Characteristic source 16
PHUSE EU 2013 Posch-Bauer Seamless Test with SAS Antonio Nieto,
Javier Gómez		 source
presentation source		 4
PharmaSUG 2013 Combining Analysis Results from Multiply Imputed Categorical Data Bohdana Ratitch,
Ilya Lipkovich,
Michael O'Kelly		 source 19
SGF 2013 Assessing Drug Safety with Bayesian Hierarchical Modeling Using PROC MCMC and JMP Richard C. Zink source 13
SGF 2013 Targeting Public Value in New Zealand Michael O'Neil source 4
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
NESUG 2012 A SAS Program to Construct Simultaneous Confidence Intervals of Relative Risk for Multiple Adverse Events Xiaoli Lu 6
SESUG 2012 PROC TTEST (Old Friend), What Are You Trying to Tell Us? Diep T. Nguyen source 12
SESUG 2012 Sample Size Determination for a Nonparametric Upper Tolerance Limit for any Order Statistic Dennis J. Beal source 8
MWSUG 2012 ROC Analysis for the Evaluation of Ethyl Glucuronide (EtG) as a Long-term Alcohol Biomarker in Hair and Fingernails: Evidence from a Large College Drinking Study Daniel Fuhrmann,
Michael Fendrich,
Lisa Berger,
Charles Plate,
Doug Lewis,
Joseph Jones		 10
SGF 2012 A Generalized Approach to Estimating Sample Sizes Wuchen Zhao,
Arthur X. Li		 source 7
SGF 2012 A Simple Way to Program Power Calculations Robert Lew,
Hongsheng Wu		 source 16
SGF 2012 An Advanced, Multi-Featured Macro Program for Reviewing Logs Chris Swenson source 7
SGF 2012 Use of Cutoff and SAS Code Nodes in SAS Enterprise Miner to Determine Appropriate Probability Cutoff Point for Decision Making with Binary Target Models Yogen Shah source 6
SCSUG 2011 Use of Cutoff and SAS Code node in SAS Enterprise Miner to determine appropriate probability cutoff point for decision making with binary target models Yogen Shah source 7
WUSS 2011 Boost your confidence in a 2x2 standard table Iuliana Barbalau source 8
WUSS 2011 Estimating Sample Size through Simulations Wuchen Zhao source 6
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
PharmaSUG 2011 Clinical Trials Versus Health Outcomes Research: SAS/STAT Versus SAS Enterprise Miner Patricia B. Cerrito source 15
PharmaSUG 2011 Estimating Sample Size through Simulations Wuchen Zhao,
Arthur X. Li		 source 6
SGF 2011 Detecting and Preventing Fraud in Financial Institutions Ellen Joyner source 16
SGF 2011 Living with Generalized Linear Mixed Models Walter W. Stroup source 18
SGF 2011 Taking Disease and Health Management Analytics into the Next Generation George S. Habek source 13
NESUG 2010 Sensitivity, Specificity, Accuracy, Associated Confidence Interval And ROC Analysis With Practical SAS Implementations Ning Wang,
Nancy N. Zeng,
Wen Zhu		 9
WUSS 2010 Data Visualization: "Every Picture Tells a Story" or "Putting Atomic Numbers on Your Socks"? AnnMaria De Mars source 11
WUSS 2010 Fuzzy Hierarchical Merge Algorithm with Boundary Conditions Dale Harrington source 4
WUSS 2010 Planned Contrasts and Post Hoc Tests in MANOVA Made Easy Chii-Dean Joey Lin source 8
MWSUG 2010 Medical Guidelines: Consensus Panel Versus Healthcare Analytics Patricia B. Cerrito 17
MWSUG 2010 Plotting Summary ROC Curves from Multiple Raters Using the SmryROCPlot Macro Matthew T. Karafa,
Nancy Obuchowski		 10
SESUG 2010 Detecting Medicaid Data Anomalies Using Data Mining Techniques Shenjun Zhu,
Qiling Shi,
Aran Canes		 source 9
SESUG 2010 Sample Size Calculation to Evaluate Mediation Analysis Rajendra Kadel source 12
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 2010 Using New JMP Interactive Modules to Teach Concepts in Introductory Statistics Amy G. Froelich,
William M. Duckworth		 source 9
SCSUG 2009 Techniques for Merging Datasets Based on Key Text Fields that Don't Quite Match Steve Fleming 12
PHUSE EU 2009 Analysis of a 3-period 2-treatment pharmacokinetic study to assess scaled average bioequivalence Jochen Müller-Cohrs source 11
MWSUG 2009 Group Sequential Analysis Using the New SEQDESIGN and SEQTEST Procedures Yang Yuan 20
MWSUG 2009 Predictive Modeling in Enterprise Miner Versus Regression Patricia B. Cerrito 27
SGF 2009 Designing Experiments for the Process George A. Milliken source 27
SGF 2009 Group Sequential Analysis Using the New SEQDESIGN and SEQTEST Procedures Yang Yuan source 20
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
SGF 2009 The Problem of Regression Assumptions and the Use of Predictive Modeling Patricia B. Cerrito source 20
PHUSE EU 2008 ETL and Data Quality: Which Comes First? Gregory S. Barnes Nelson,
Emilio J. Power		 source 10
PHUSE EU 2008 Evaluation of Diagnostic Agents: a SAS Macro for Sample Size Estimation Using Exact Methods Stefano Vezzoli source 8
MWSUG 2008 The Difference Between Predictive Modeling and Regression Patricia B. Cerrito 19
PharmaSUG 2008 ETL and Data Quality: Which Comes First? Emilio J. Power,
Gregory S. Barnes Nelson		 10
SGF 2008 A Macro for Getting More out of Your ROC Curve Jennifer Lambert,
Ilya Lipkovich		 source 11
SGF 2008 ETL and Data Quality: Which Comes First? Emilio J. Power,
Gregory S. Barnes Nelson		 source 10
SGF 2008 How to Use SAS to Fit Multiple Logistic Regression Models Anpalaki J. Ragavan source 13
NESUG 2007 Summarizing the Power of Your Predictive Model with Receiver Operating Characteristic Curves Mithat Gonen 18
MWSUG 2007 RANDOM and REPEATED statements - How to Use Them to Model the Covariance Structure in Proc Mixed Charlie Liu 11
WUSS 2007 Statistical Inference Illustrated Richard R. Allen source 19
PNWSUG 2007 Multiple comparisons on 2xc proportions John Horne 12
PHUSE EU 2006 Analysis of incomplete two-period crossover trials with SAS PROC MIXED Jochen Müller-Cohrs source 8
NESUG 2006 Receiver Operating Characteristic (ROC) Curves Mithat Gonen 18
PharmaSUG 2006 Searching for the Right Search Tool Eugene Yeh,
Angela S. Ringelberg		 12
PharmaSUG 2006 Simple Tests of Hypotheses for the Non-statistician: What They Are and Why They Can Go Bad Arthur L. Carpenter 9
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 Estimate the False Discovery Rate Using SAS Jason A. Osborne source 10
SUGI 2006 METAPERM2: A SAS Macro for Permutation Tests of Linear Models in Fixed and Random Effects Meta-Analyses Jeffrey D. Kromrey,
Kristine Y. Hogarty		 source 10
SUGI 2006 Receiver Operating Characteristic (ROC) Curves Mithat Gonen source 18
SUGI 2006 Simple Tests of Hypotheses for the Non-statistician: What They Are and Why They Can Go Bad Arthur L. Carpenter source 9
SESUG 2005 Use a SAS Database Search Engine Instead of Writing a Program Eugene Yeh source 10
PHUSE EU 2005 Power calculation of non-inferiority trials assuming poisson distributions Corinna Miede,
Jochen Müller-Cohrs		 source 11
WUSS 2005 Simple Tests of Hypotheses for the Non-statistician: What They Are and Why They Can Go Bad Arthur L. Carpenter source 9
SUGI 2005 Estimation of Type III Error and Power for Directional Two-Tailed Tests Using PROC POWER Cam-Loi Huynh source 10
NESUG 2004 Perusing, Choosing, and Not Mis-using: Non-parametric vs Parametric tests in SAS Venita DePuy,
Paul Pappas		 5
SCSUG 2004 Designing the Optimal File Linkage Algorithm (OFLA) [ Poster ] Tsai Mei Lin 14
MWSUG 2004 Calculation and Assessment of Inferential Test Statistics for Meta Analysis of Cross-Over Clinical Trials Hurley 8
SUGI 2004 An Animated Guide: The Logic of Hypothesis Testing and ANOVA Russell M. Lavery source 11
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
SESUG 2003 METAPERM: A SAS Macro for Permutation Tests of Linear Models in Meta-analysis Jeffrey D. Kromrey,
Kristine Y. Hogarty		 source 6
NESUG 2003 An Animated Guide: The Logic of Hypothesis Testing and ANOVA Russell M. Lavery 7
SEUGI 2003 SAS Interaction Management [presentation] Jens Echtermeyer source 22
SEUGI 2003 The Topic Scoring Engine [presentation] Ulrich Reincke source 37
SEUGI 2003 Uncovering the Hidden Fiance Crime - the SAS Anti-Money Laundering Solution [presentation] Sascha Schubert source 39
SUGI 2003 A SAS/IML Program for Mapping QTL in Line Crosses Chenwu Xu,
Shizhong Xu		 source 6
NESUG 2002 Visual Optimization: Using SAS And Java To Explore High Density Data In Equity Portfolios Haftan M. Eckholdt,
Ezra Benun		 5
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
SEUGI 2002 Closing the loop on Fraud [presentation] Anton Hirschowitz source 27
MWSUG 2001 A Basic Mathematical Explanation of the SAS / QC and PROC Shewhart Jim Edgington 3
NESUG 2001 Lost in Space: Recovering unmeasured dimensions in spatial studies Haftan M. Eckholdt 8
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 Study the Gender and Level Measurement Equivalence of a Multi-rater Survey Jim Penny 6
SEUGI 2001 SAS and CFMS Integration - Attacking Fraud in Next Generation Networks [presentation] Augusto Argento source 35
SUGI 2001 A Basic Mathematical Explanation of SAS/QC and PROC SHEWHART James F. Edgington source 3
SUGI 2001 Approximations to Distributions of Test Statistics in Complex Mixed Linear Models Using SAS PROC MIXED G. Bruce Schaalje source 6
SEUGI 2000 An ordered list of customers for a new Bank: scoring with EM 3.0 [presentation] Flavio Bonifacio source 14
NESUG 1999 Visual Analysis on the WEB: Animating High Density Multidimensional Data Haftan M. Eckholdt 9
SUGI 1999 Use of Enterprise Miner and Multivariate Statistical Analysis to Build Fraud-Detection Models Shiao-Ping Lu source 5
MWSUG 1998 Producing ROC Curves For Discriminant Analysis Using PROC LOGISTIC Keith Dunnigan 7
WUSS 1998 Use of Data Enterprise Miner & Multivariate Statistical Analysis to Build Fraud-Detection Models Shiao-Ping Lu source 7
SESUG 1998 Multiple Comparison Procedures with SAS Chung-Kuei Chang 9
SUGI 1998 How to Use SAS Software to Evaluate Screening Tests Using Predictive Values in Conjunction with ROC Curves Richard Severino source 6
WUSS 1997 How to Use the SAS Software to Evaluate Screening Tests Using Predictive Values in Conjunction with ROC Curves Richard Severino source 7
WUSS 1997 Logistic Regression Modeling in Complex Surveys: Examples Using LOGITSE SAS Macro Jesse Albert Canchola,
Brian D. Marx,
Joseph A. Catania		 source 10
SESUG 1997 Identifying Clinical Practice Improvement Opportunities Using Resampling Techniques in PROC MULTTEST Gregory L. Pearce 6
PharmaSUG 1997 Controlling for Experimentwise Type II Error: Optimum Patient Allocation for a Three Armed, Parallel, Randomized, Controlled Clinical Trial with Binary Outcomes Benjamin Duncan 13
SUGI 1997 Constructing ROC Curves with the SAS System Andrew G. Stead,
Karen G. MacDonald		 source 4
SUGI 1997 Using Resampling Techniques in PROC MULTITEST to Evaluate Surgeon SpecificResults Following Coronary Artery Bypass Graft (CABG) Surgery Gregory L. Pearce,
Peter H. Westfall		 source 5
SESUG 1996 Stepwise Regression as a Multiple Comparison Procedure Rodney Sparapani 3
NESUG 1996 Between a ROC Curve and a Hard Place Joseph Kufera,
Kimberly A. Mitchell		 10
SEUGI 1995 A Simulation Study Using the SAS System - Stepwise Rejective Stopping Boundaries for Clinical Trials with Multiple Treatments Barbara G. Schneider source 11
SEUGI 1994 A Graphic Approach to the Evaluation of the Performance of Diagnostic Tests Using SAS Software Renza Cristofani source 9
MWSUG 1993 Designing Bank Warning System Based on Logit Model Fitted to Multi-Period Performance Data Sameer Kumar,
Sant R. Arora		 10
SEUGI 1993 The Closed Test Procedure Hans Ulrich Burger source 13
SUGI 1993 An Interactive SAS/AF System for Sample Size Calculation Deborah J. Matos source 6
SUGI 1992 Using SAS Software to Evaluate the Imaging Performance of Presurgical Diagnostic Tests in the Detection of Cancer Kristin R. Dawson source 7
NESUG 1991 Profiling and Rebundling Medical Care Claims Using the FORMAT Procedures and Macros Michael L. Davis 6
SUGI 1990 Hypotheses and Sample Size for Showing Equivalence James J. Ashton source 5
SUGI 1990 Performance of Multiple Comparisons in Repeated Measures Designs under Nonsphericity Steven F. Thomson source 6
SUGI 1989 P-Value Adjustments for Multiple Tests in Multivariate Binomial Models Peter H. Westfall,
S. Stanley Young		 source 4
SUGI 1988 Type I Error Rate for Small Sample Sizes Using Various Options of the CATMOD Procedure J. Paul Costiloe,
Andrew J. Cucchiara,
Susan J. Kenny		 source 4
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 1984 Generating Bivariate Exponential Distributions via SAS Macros with Application to Repeated Measures Designs Melvin Moeschberger,
P. K. Tandon		 source 4
SUGI 1983 Practical Methods for Multiple Comparisons in MANOVA Keith E. Muller source 4
SUGI 1981 Type I Error Rates for the Unequal Variance T Test J. Philip Miller,
Robert P. Parks,
Reimut Wette		 source

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