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proc iml

160 papers and 6 presentations; 157 titles.

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Conference × Year × Title × Authors Extras Pages
PharmaSUG 2026 Enhancing CDISC Standards Implementation (SDTM and ADaM) with PROC FCMP, PROC IML and Macro Loop Integration in Oncology Clinical Trials. Ajay Gupta,
Misikir Tesfaye		 source 7
PharmaSUG 2026 Implementing Dynamic Time Warping in SAS 9.4 Using PROC IML: An Alternative Approach for Time-Series Model Evaluation Yida Bao,
Philippe Gaillard,
Wei Yao,
Zheng Zhang,
Rui Wang		 source 13
PHUSE EU 2025 A New Gateway to Open Source in SAS Jim Box source
presentation source		 7
PHUSE EU 2025 R Adoption and Change Management A Large CRO Perspective Martin Brown,
Lynn Clipstone		 source
presentation source		 8
PharmaSUG 2025 A New Gateway to Open Source in SAS Viya Jim Box,
Mary Dolegowski		 source 7
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 Route Sixty-Six to SAS Programming, or 63 (+3) Syntax Snippets for a Table Look-up Task, or How to Learn SAS by Solving Only One Exercise! Bartosz Jabłoński,
Quentin McMullen		 source 58
WUSS 2024 Fifty Shades of SAS Programming, or 53 (+3) Syntax Snippets for a Table Look-up Task, or How to Learn SAS by Solving Only One Exercise! Bartosz Jabłoński,
Quentin McMullen		 source 50
WUSS 2024 Matrices and More: An Overview of the SAS/IML Language [presentation] Rick Wicklin source 46
WUSS 2024 Simulation in SAS for Estimating Power [presentation] Michael Williams source 18
PharmaSUG CN 2024 Automatically generation of shell-driven TFLs with R and SAS Hang Sun,
Yi Yang,
Yu Li		 source 6
PharmaSUG CN 2024 Exploring the Interaction Between SAS and R to Enhance Programming Efficiency Qi Zhai,
Yu Li,
Yi Yang		 source 8
PharmaSUG 2024 Estimating Time to Steady State Analysis in SAS Richard Moreton,
Lata Maganti		 source 8
PHUSE US 2024 A Larger Tent - Integrating Multiple Open-Source Environments in SAS [presentation] Sundaresh Sankaran,
Samiul Haque		 source 15
WUSS 2023 The Delta Method in Statistical Inference, with Applications in the SAS IML Procedure Carter Sevick,
Camille Moore,
Samantha MaWhinney		 source 14
PharmaSUG 2023 Using the R interface in SAS to Call R Functions and Transfer Data Bruce F. Gilsen source 16
PHUSE EU 2022 Minimising 'Data Loss' During Mapping of Raw Data to SDTM [presentation] John Monaghan source
video		 35
SESUG 2022 A SAS Macro to Calculate Blinding Index in Clinical Trials: %blinding_index, an application of PROC IML Jingwei Wu,
Di Zhu		 source 7
WUSS 2022 SAS and Open Source Playing Nicely Together Jim Box,
Samiul Haque		 source 9
SESUG 2021 Missing Value Imputation Ross Bettinger source 34
PharmaSUG 2021 An R Shiny Application: Validated Analysis Results Using R and SAS Abu Zafar Mohammad Sami source 9
SGF 2020 Bayesian Sequential Monitoring of Clinical Trials Using SAS Matthew A. Psioda source 13
SGF 2020 Play More, Achieve More: Training the Next Generation of Data Analysts Through Strategic Gaming Hillary Graham source 11
SGF 2020 Pricing Life Insurance Contracts with Early Exercise Features Using Neural Networks Helgard Raubenheimer source 9
SGF 2020 Simulating Data for Complex Linear Models Phil Gibbs,
Kathleen Kiernan		 source 20
SGF 2020 Using the R interface in SAS to Call R Functions and Transfer Data Bruce F. Gilsen source 17
SGF 2020 Write Custom Parallel Programs by Using the iml Action Rick Wicklin,
Arash Dehghan Banadaki		 source 18
PharmaSUG 2020 Effective Exposure-Response Data Visualization and Report by Combining the Power of R , SAS programming and VBScript Shuozhi Zuo,
Hong Yan		 source 11
PHUSE EU 2019 Efficiently Simulating Normally Distributed Data for Animation Benjamin White source
poster source		 14
SESUG 2019 Using the R interface in SAS to Call R Functions and Transfer Data Bruce F. Gilsen source 17
WUSS 2019 Everything Is Better with Friends: Executing SAS Code in Python Scripts with SASPy Isaiah Lankham source 20
WUSS 2019 Working with Sparse Matrices in SAS Andrew T. Kuligowski,
Lisa A. Mendez		 source 9
PharmaSUG 2019 Application of R Functions in SAS to Estimate Dose Limiting Toxicity Rates for Early Oncology Dose Finding Huei-Ling Chen,
Zhen Zeng		 source 9
SGF 2019 Everything Is Better with Friends: Executing SAS Code in Python Scripts with SASPy Isaiah Lankham,
Matthew T. Slaughter		 source 20
SGF 2019 Using the R interface in SAS to Call R Functions and Transfer Data Bruce F. Gilsen source 17
SESUG 2018 Interrelationship Digraphs and Sociograms Using SAS Melvin T. Alexander source 18
SESUG 2018 Using the R interface in SAS to Call R Functions and Transfer Data Bruce F. Gilsen source 17
MWSUG 2018 Application of heavy-tailed distributions using PROC IML, NLMIXED and SEVERITY Palash Sharma 14
WUSS 2018 SAS Techniques to Handle Large Files And Reduce Execution times Kaiqing Fan source 7
WUSS 2018 Using PROC MCMC in a Process Control Setting: An Illustrative Example with PROC IML Austin R. Brown source 8
SGF 2018 Alternative Variance Parameterizations in Count Data Models Robin High source 14
SGF 2018 Using the IML Procedure to Examine the Efficacy of a New Control Charting Technique Austin R. Brown source 8
SESUG 2017 A SAS macro replacement for Dynamic Data Exchange (DDE) for use with SAS grid computing Saki Kinney,
David Wilson,
Benjamin Carper		 source 9
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
MWSUG 2017 Unconventional Statistical Models with the NLMIXED Procedure Robin High 14
WUSS 2017 Examining the Performance of a Control Chart for the Shifted Exponential Distribution using Penalized Maximum Likelihood Estimators: A Simulation Study using SAS Austin R. Brown,
Bryce Whitehead		 source 8
PharmaSUG 2017 REDCAP Ins and Outs Leanne Goldstein source 10
SGF 2017 Cold-Start Solution to A/B Testing Using Adaptive Sample Size Modification Bo Zhang,
Liwei Wang		 source 9
SGF 2017 More Than Matrices: SAS/IML Software Supports New Data Structures Rick Wicklin source 19
SGF 2017 Using Vibration Spectral Analysis to Predict Failures by Integrating R into SAS Asset Performance Analytics Adriaan Van Horenbeek source 15
SCSUG 2016 Ten Tips for Simulating Data with SAS Rick Wicklin source 15
MWSUG 2016 Establishing Similarity of Modeled and Experimental PK/PD Hysteretic Loops using Pseudo Time Series Analysis and Dynamic Time Warping Ron Smith 18
PharmaSUG CN 2016 Hands-on Example of Matrix Operation in SAS with Different Approaches Huan Cheng 7
WUSS 2016 Contributing to SAS By Writing Your Very Own Package Hunter Glanz,
Emily Johnson		 source 5
WUSS 2016 SAS Graphing Done Right: Two Good Alternatives to PROC GPLOT/GCHART, Part 2 Isaiah Lankham source 17
PharmaSUG 2016 SAS and R - stop choosing, start combining and get benefits! Diana Bulaienko source 7
SGF 2016 Diagnosing Obstructive Sleep Apnea: Using Predictive Analytics Based on Wavelet Analysis in SAS/IML Software and Spectral Analysis in PROC SPECTRA Woranat Wongdhamma source 12
SGF 2016 Integrating SAS and R to Perform Optimal Propensity Score Matching Lucy D'Agostino McGowan,
Robert Greevy		 source 11
SGF 2016 MCMC in SAS: From Scratch or by PROC Chelsea Lofland source 19
SGF 2016 Upgrade from ARIMA to ARIMAX to Improve Forecasting Accuracy of Nonlinear Time-Series: Create Your Own Exogenous Variables Using Wavelet Analysis Woranat Wongdhamma source 16
SGF 2016 Writing Packages: A New Way to Distribute and Use SAS/IML Programs Rick Wicklin source 10
WUSS 2015 SAS at Los Angeles County Assessor's Office Anthony Liu source 20
WUSS 2015 SAS Graphing Done Right: Two Good Alternatives to PROC GPLOT/GCHART Isaiah Lankham source 12
SGF 2015 Permit Me to Permute: A Basic Introduction to Permutation Tests with SAS/IML Software John Vickery source 15
SGF 2015 Ten Tips for Simulating Data with SAS Rick Wicklin source
zip		 15
SESUG 2014 Evaluating Additivity of Health Effects of Exposure to Multiple Air Pollutants Given Only Summary Data Pollutants Given source 9
SESUG 2014 Integrating Data and Variables between SAS and R via PROC IML: Enable Powerful Functionalities for Coding in SAS Feng Liu,
Ruiwen Zhang		 source 4
MWSUG 2014 Using The Delta Method With Proc Mixed To Generate Means And Confidence Intervals From A Linear Mixed Model On The Original Scale, When The Analysis Is Done On The Log Scale Brandy R. Sinco,
Edith Kieffer,
Michael S. Spencer		 11
WUSS 2014 Using R in the SAS System Alan Mitchell source 9
WUSS 2014 Using SAS to do it all Chelsea Lofland,
Rebecca Ottesen		 source 16
SGF 2014 Getting Started with the SAS/IML Language Rick Wicklin source 21
SGF 2014 Modeling Loss Given Default in SAS/STAT Xiao Yao,
Jonathan Crook,
Galina Andreeva		 source 9
SGF 2014 Recommending News Articles Using Cosine Similarity Function Rajendra Ledalla Venkata Naga,
Qing Wang,
John Dilip Raj		 source 7
SESUG 2013 Using Predetermined Factor Structures to Simulate a Variety of Data Conditions Kevin Coughlin,
Fort Myers		 source 12
PharmaSUG 2013 More Power to SAS - Embedding Other Programming Languages in SAS Through SAS/IML Studio Max Cherny source 10
SGF 2013 Analyzing Partially Confounded Factorial Conjoint Choice Experiments Using SAS/IML Chin Khian Yong,
Song Lin Ng		 source
pdf		 11
SGF 2013 Getting Started with the SAS/IML Language Rick Wicklin source 21
SGF 2013 Optimize SAS/IML Software Codes for Big Data Simulation Chao Huang,
Goutam Chakraborty,
Yu Fu		 source
pdf		 7
SGF 2013 Using SAS to Measure Airport Connectivity: An Analysis of Airport Centrality in the US Network with SAS/IML Studio Augusto Voltes-Dorta,
Hector Rodriguez-Deniz,
Pere Suau-Sanchez		 source 14
NESUG 2012 Penetrating the Matrix Justin Smith,
William 'Gui' Zupko II		 11
SESUG 2012 Random Effects Simulation for Sample Size Calculations Using SAS Random Effects Simulation source 11
WUSS 2012 SAS "IML" (Introduction at the Master's Level) Anton Bekkerman source 5
PharmaSUG CN 2012 An Illustration of Rate Difference Estimation with SAS in Logistic Regression Yun Guo,
Victor Wu,
Xinyu Xu,
Crystal Cheng		 ppt 7
PharmaSUG 2012 Scrambling of Un-Blinded Data without 'Scrambling Data Integrity'! Jaya Baviskar source 8
PharmaSUG 2012 Tumor Assessment using RECIST: Behind the Scenes Suhas R. Sanjee,
Rajavel Ganesan,
Mary N. Varughese		 source 7
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 Transforming Variables for Normality and Linearity - When, How, Why and Why Not's Steven M. LaLonde source 8
SGF 2012 Using SAS to Measure Airport Connectivity: An Application of Weighted Betweenness Centrality for the FAA National Plan of Integrated Airport Systems (NPIAS) Hector Rodriguez-Deniz source 12
SESUG 2011 Acknowledging the Unknown: A SAS Macro for Investigating Omitted Variable Bias in Two-Level Linear Models Jason A. Schoeneberger,
Bethany A. Bell,
Jeffrey D. Kromrey		 source 16
PHUSE EU 2011 Calling R Functions from SAS Peter Bewerunge source
presentation source		 7
PharmaSUG 2011 Formulas Calculating Risk Estimates and Testing for Effect Modification and Confounding Manojkumar B Agravat source 44
PharmaSUG 2011 Using SAS for Modeling and Simulation in Drug Development - A Review and Assessment of Some Available Tools Melvin S. Munsaka,
Michael Carniello		 source 10
SGF 2011 Developing User-Defined Functions in SAS: A Summary and Comparison Songfeng Wang,
Jiajia Zhang		 source 9
NESUG 2010 Visualizing Bi-partite Network Data using SAS Visualization Tools John Zheng 10
SCSUG 2010 Retrieving Sound Information from MIDI and Other Multivariate Data: SAS to the Rescue Cecil R. Hallum source 22
WUSS 2010 Rediscovering SAS/IML Software: Modern Data Analysis for the Practicing Statistician Rick Wicklin source 18
WUSS 2010 Statistical Modeling of the Mechanical Behavior of Spring, Mass and Damper Assembly Using SAS Anpalaki J. Ragavan source 11
MWSUG 2010 Novel Use of SAS Software in Industrial and Biomedical Consulting, Research, and Teaching Timothy E. O'Brien 13
MWSUG 2010 Tips for Automating Univariate Outcomes Analysis in Hematopoietic Stem Cell Transplantation Peigang Li,
Xiaochun Zhu,
Min Chen		 7
PharmaSUG 2010 Do you want to do Matrix Calculations with Base SAS Software without SAS/IML? No Worries. Sarfaraz Sayyed,
Binoy Varghese		 11
PharmaSUG 2010 ECG Feature Detection Using SAS Suhas R. Sanjee,
Sridhar Vijendra		 9
SGF 2010 Rediscovering SAS/IML Software: Modern Data Analysis for the Practicing Statistician Rick Wicklin source 18
SGF 2010 Statistical Modeling of the Mechanical Behavior of Spring, Mass and Damper Assembly Using SAS Anpalaki J. Ragavan source 11
PharmaSUG 2009 Translation of Drug Metabolic Enzyme and Transporter (DMET) Genetic Variants into Star Allele Notation using SAS Mark Farmen 17
PharmaSUG 2009 Using SAS/IML to Generate Weighted Chi-Square Statistics Daniel DiPrimeo,
Bruce Johnston,
Lisa Price,
Junming Yang		 8
SGF 2009 A SAS Macro for Adaptive Regression Modeling George J. Knafl source 9
WUSS 2008 Score Test of Proportionality Assumption for Cox Models Xiao Chen source 6
PharmaSUG 2008 Display gene network using Data Step Graphics Interface (DSGI) Wenjie Song,
Ke Yang		 7
SGF 2008 SAS Performance Monitoring: A Deeper Discussion Tony Brown source 25
SESUG 2007 ROBUST_ES: A SAS Macro for Computing Robust Estimates of Effect Size Jeffrey D. Kromrey,
Kevin B. Coughlin		 source 16
MWSUG 2006 That's the Signpost Up Ahead Your Next Stop, SAS IML Gary Allen 10
SESUG 2006 Generating Multivariate Normal Data by Using PROC IML Lingling Han source 6
SUGI 2006 The "Handy, Dandy, Quick-n-Dirty" Contrast Generator - A SAS/IML Macro to Support the GLM, MIXED, and GENMOD Procedures Paul A. Thompson source 10
WUSS 2005 Can Matrix Capture Missing Data Values? Keh-Dong Shiang source 9
NESUG 2005 SAS BI on Steroids Florio Arguillas,
Kevin Huddleston		 9
NESUG 2005 Transforming Variables for Normality and Linearity - When, How, Why and Why Not's Steven M. LaLonde 8
PharmaSUG 2005 Calculating Posterior Probability of the Maximum Contrast Using PROC IML Akira Wakana,
Isao Yoshimura,
Chikuma Hamada		 6
SUGI 2005 Testing the Hypothesis of a Kroneckar Product Covariance Matrix in Multivariate Repeated Measures Data Anuradha Roy,
Ravindra Khattree		 source 11
PharmaSUG 2004 Statistical Simulations for Sample Size Calculation with PROC IML Izabella Peszek 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 Variance Estimates for Census 2000 Using SAS/IML Software Peter P. Davis source 6
NESUG 2001 Using Taylor's Linearization Technique in StEPS to Estimate Variances for Non-Linear Survey Estimators Roger L. Goodwin 10
WUSS 2001 SAS Direct (Kronecker) Product Techniques Applied to Design Matrices in a Two-Way Cross Classification Balanced Model Example Steven Hoff source 5
SEUGI 1999 Boosting your SAS/AF applications with the power of the WIN32 API [presentation] Martin Sjoholm source 14
SEUGI 1999 Costing Warehouse Resources - A Solution for Windows NT Server [presentation] Michael Matthews source 34
SUGI 1999 Stepwise Regressor Selection for Interdependence Analysis and Multivariate Multiple Regression James E. Dunn,
Lynette K. Duncan		 source 6
WUSS 1998 A PROC IML Macro for Detecting Health Care Fraud Jimmy Thomas Efrid source 3
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
WUSS 1998 Using PROC IML to Rank Scores Karen Walker source 4
NESUG 1998 Using SAS/IML to Calculate L-Moments for the Univariate Distribution Shape Parameters Skewness and Kurtosis Michael A. Walega 8
SUGI 1998 A Macro for Converting Mean Separation Output to Letter Groupings in PROC MIXED Arnold M. Saxton source 4
SCSUG 1997 A Generalization of the Stuart-Maxwell Test Stephen I. Black,
Mithat Gonen		 14
SUGI 1997 Power Transformations Using SAS/IML Software Ioannis C. Dimakos source 4
SUGI 1997 Using Higher Order Asymptotics to Improve P-values and Confidence Intervals Given by PROC MIXED Ben Lyons,
Dawn Peters		 source 5
SUGI 1997 Using Linear Regression and the Gibbs Sampler to Estimate the Probability of a Part Being Within Specification Brenda Cantell source 6
SESUG 1996 Computing A DB-Optimal Design Augmentation Scheme Using PROC Il\1L (And Why SAS/QC Can't Do It) Paul T. Savarese 6
SUGI 1996 A Study of Kinetics: The Estimation and Simulation of Systems of First Order Differential Equations Donald Erdman,
Maurice M. Morelock		 source 8
SUGI 1996 Using SAS Software to Assess and Adjust for Nonlinearity in Nonlinear RegreSSion Models Timothy E. O'Brien,
Ye Wang		 source 10
MWSUG 1995 Simulation and Bootstrapping in the SAS System: A tutorial using PROC IML Paul A. Thompson 10
SESUG 1995 Posters The MODULE function in SAS 6.10: An OS/2 Experience Francis J. Kelley 10
SUGI 1995 Designer Graphics: Anatomy of Some SAS Macros for Statistical Graphics Michael Friendly source 8
WUSS 1994 A Matrix Approach to Log-Linear Data Analysis Using SAS/IML Paul W. Johnson source 3
SUGI 1994 A Comparison of the GLM, IML, and MIXED Procedures for Use in Spatial Statistical Analyses William J. Price,
Bahman Shafii		 source 6
NESUG 1993 Use of PROC IML to Calculate L-Moments for the Univariate Distributional Shape Parameters Skewness and Kurtosis Michael A. Walega 8
SUGI 1993 Applications of the IML Procedure for Multiple Response Permutation Tests William D. Johnson,
Donald E. Mercante		 source 5
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
MWSUG 1992 Using PROC IML to do Matrix Balancing Carol Alderman 6
SEUGI 1992 Using SAS Macros and PROC IML to Create Special Designs for Use in Generalised Linear Models John Hendrickx source 22
SEUGI 1992 Using SAS/IML for Advanced Statistical Needs, With an Example on Credit Scorecard Building Lynne Pritchard,
Paul Chik		 source 10
SUGI 1992 A SAS Macro for Performing Analyses of Random Effect Models of Longitudinal Data Using the IML Procedure Greg A. Grandits,
Patricia Grambsch,
Thomas Louis		 source 6
SUGI 1992 SAS/IML Software: An Application-Oriented Introduction Ed Barber source 4
SUGI 1992 Using the NLIN Procedure to Combine Estimates of Relative Potency Stan Altan,
Jaya Natarajan		 source 6
MWSUG 1991 Consumer Demand Preference Patterns: Using PROC IML to Forecast Future Demand Daric Brummett,
Lawrence C. Marsh		 5
SUGI 1991 Econometric Modeling of Sweetgum Stem Biomass Using the IML and SYSLIN Procedures Bernard R. Parresol,
Charles E. Thomas		 source 6
SUGI 1991 Using the IML Procedure for Iteratively Reweighted Multiple Linear Regression with a Block-diagonal Covariance Matrix Donald H. MacQueen source 5
SEUGI 1990 The Analysis of Multiple Endpoints in Clinical Trials Lars Frison source 8
SUGI 1990 The Calculation of Average Run Length for a Nonparametric CUSUM Procedure Dennis W. King,
Michael T. Longnecker		 source 7
SUGI 1990 What SAS/IML Software Has to Offer beyond the MATRIX Procedure Donna E. Woodward source 7
SUGI 1989 Estimating the Translog Functional Form and Calculating Elasticities with Standard Errors: An Application of the IML Procedure Gary S. Klonicki source 6
SUGI 1988 Extending the SAS System on Microcomputers with SAS/IML Software, the Interactive Matrix Language Linda P. Atkinson source 10
SUGI 1988 SAS/IML Software versus IBM/APL as a Scientific Programming Language Stephanie Breytenbach,
Gordon Erens		 source 4
SUGI 1987 Using SAS/IML ""Software - A Multivariate Control Chart Example Phil Cirulli source 3
SEUGI 1986 An Introduction to SAS/IML Software, an Interactive Matrix Language Mogens Weinreich source 8
SEUGI 1986 Generalized Linear Models in SAS Using PROC GLM James Roger source 10
SUGI 1986 How Will SAS Software for the Microcomputer and Organizations Come to Grips with Each Other? Charles F. Hofacker,
Paul Hoffman		 source 3
SEUGI 1985 First Impressions of the SAS System - Version 5 Phil Davies source 10

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