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306 papers; 239 titles.

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Conference × Year × Title × Authors Extras Pages
WUSS 2026 The (ODS) Output of Your Desires: a Tool-kit for Creating Designer Reports and Data Sets Louise S. Hadden source 12
PharmaSUG 2026 SAS and R for Expanding Data for Pharmacometrics Analysis (PMx) Analysis Data Sets Jeffrey Rathbun,
Rebecca Humphrey		 source 8
PharmaSUG 2026 The (ODS) Output of Your Desires: Creating Designer Reports and Data Sets Louise S. Hadden source 12
PHUSE US 2026 Geocoding with the Google Maps API: Using PROC FCMP To Call User-Defined SAS and Python Functions That Geocode Coordinates into Addresses, Calculate Routes, and More! Troy Martin Hughes source
presentation source		 15
MWSUG 2025 Geocoding with the Google Maps API: Using PROC FCMP To Call User-Defined SAS and Python Functions That Geocode Coordinates into Troy Martin Hughes source 14
MWSUG 2025 The (ODS) Output of Your Desires: Creating Designer Reports and Data Sets Louise S. Hadden source 12
SESUG 2025 Geocoding with the Google Maps API: Using PROC FCMP To Design User-Defined SAS Subroutines That Call User-Defined Python Functions That Geocode Coordinates into Addresses, Calculate Routes, and More! Troy Martin Hughes 14
SESUG 2025 The (ODS) Output of Your Desires: Creating Designer Reports and Data Sets Louise S. Hadden 12
WUSS 2025 The (ODS) Output of Your Desires: Creating Designer Reports and Data Sets Louise S. Hadden source 12
PharmaSUG 2025 An Introduction to Obtaining Test Statistics and P-Values from SAS and R for Clinical Reporting Brian K. Varney source 9
PharmaSUG 2025 Four roads lead to Outputting Datasets Dynamically (ODDy) & Beyond Jason J. Su source 10
PharmaSUG 2025 Geocoding with the Google Maps API: Using PROC FCMP To Call User-Defined SAS and Python Functions That Geocode Coordinates into Addresses, Calculate Routes, and More! Troy Martin Hughes source 14
PharmaSUG 2025 The (ODS) Output of Your Desires: Creating Designer Reports and Data Sets Louise S. Hadden source 12
MWSUG 2024 An Introduction to Obtaining Test Statistics and P-Values from SAS and R Brian K. Varney source 9
SESUG 2024 An Introduction to Obtaining Test Statistics and P-Values from SAS and R Brian K. Varney source 6
WUSS 2024 The SAS Supervisor Donald J. Henderson source 13
PharmaSUG 2024 Integrity, Please: Three Techniques for One-Step Solution in Pharmaceutical Programming Jason J. Su source 15
PharmaSUG 2023 An Introduction to Obtaining Test Statistics and P-Values from SAS and R for Clinical Reporting Brian K. Varney source 9
PharmaSUG 2023 Repetitive Analyses in SAS - Use of Macros Versus Data Inflation and BY Group Processing Bradford J. Danner,
Indrani Sarkar		 source 6
PHUSE US 2023 An Introduction to Obtaining Test Statistics and P-Values from SAS and R for Clinical Reporting Brian K. Varney source
presentation source		 6
WUSS 2022 Let SAS do the work for you: Tips and tricks for turning SAS output into client-ready tables Becky Lien,
Sara Richter,
Lily Dunk		 source 15
PharmaSUG 2022 Look Up Not Down: Advanced Table Lookups in Base SAS Jayanth Iyengar,
Joshua M. Horstman		 source 28
PharmaSUG 2022 Simple and Efficient Bootstrap Validation of Predictive Models Using SAS/STAT Software Matthew T. Slaughter,
Isaiah Lankham		 source 22
PharmaSUG 2021 Dynamic macro using the convergence dataset to generate the Odds Ratio (OR), Risk Ratio (RR) and Risk Difference (RD) per SOC/PT using Genmod procedure Jagadish Katam source 20
SGF 2021 A Framework for Simple and Efficient Bootstrap Validation in SAS, with Examples Isaiah Lankham,
Matthew T. Slaughter		 source 22
SGF 2021 Bayesian Analysis of GLMMs Using PROC BGLIMM Walter W. Stroup source
pdf		 25
SESUG 2020 Look Up Not Down: Advanced Table Lookups in Base SAS Jayanth Iyengar,
Joshua M. Horstman		 source 28
SGF 2020 Introducing the GAMSELECT Procedure for Generalized Additive Model Selection Michael Lamm,
Weijie Cai		 source 25
SGF 2020 Simple and Efficient Bootstrap Validation of Predictive Models Using SAS/STAT Software Isaiah Lankham,
Matthew T. Slaughter		 source
github		 15
PharmaSUG 2020 %MVMODELS: a Macro for Survival and Logistic Analysis Jeffrey P. Meyers source 23
SESUG 2019 Advanced Statistical Modeling within Machine Learning and Big Data Analytics Niloofar Ramezani,
George Mason		 source 16
MWSUG 2019 Look Up Not Down: Advanced Table Lookups in Base SAS Jayanth Iyengar,
Joshua M. Horstman		 24
MWSUG 2019 Using ODS Trace (DOM), Procedural Output and ODS Output Objects to Create the Output of Your Dreams Louise S. Hadden 26
WUSS 2019 Automating a Summary Report of PSM Model and Match Results Desiree Hall source 9
PharmaSUG 2019 With a Trace: Making Procedural Output and ODS Output Objects Work For You Louise S. Hadden source 26
SGF 2019 Applying Propensity Score Methods to Complex Survey Data Using PROC PSMATCH Patrick Karabon source 10
SGF 2019 Working with ODS Trace Statement and ODS Output Objects Louise S. Hadden source 26
PHUSE US 2019 Check Your Data: Tools for Automating Data Assessment Paul Stutzman source
presentation source		 10
PHUSE EU 2018 Please Put Your Data in an Upright Position - Or How to Tackle Verticalisation Kristina Zweier source
presentation source		 9
SESUG 2018 Table Taming - Using ODS to Simplify Data Presentation Emily Perry source 12
SESUG 2018 Tips and Tricks for Ensuring Accurate Routine Data Processing when Logs are Redirected to Text Files Davia N. Moyse source 7
PharmaSUG 2018 Discover the Deeper DATA Step Timothy J. Harrington source 14
PharmaSUG 2018 Manipulating Statistical and Other Procedure Output to Get the Results That You Need Vincent DelGobbo source 37
SGF 2018 Getting More Insight into Your Forecast Errors with the GLMSELECT and QUANTSELECT Procedures Gerhard Svolba source 26
SGF 2018 Manipulating Statistical and Other Procedure Output to Get the Results That You Need Vincent DelGobbo source 37
SGF 2018 Model Selection Using Information Criteria (Made Easy in SAS ) Wendy Christensen source 12
WUSS 2017 Effectively Utilizing Loops and Arrays in the DATA Step Arthur X. Li source 17
PharmaSUG 2017 Check Your Data: Tools for Automating Data Assessment Paul Stutzman source 12
PharmaSUG 2017 Deriving Rows in CDISC ADaM BDS Datasets Sandra Minjoe source 12
SGF 2017 Deriving Rows in CDISC ADaM BDS Data Sets Using SAS DATA Step Programming Sandra Minjoe source 17
SESUG 2016 Identifying Gaps in Time Series Data Identifying Gaps source 8
SESUG 2016 Tales from the Help Desk 7: Solutions to Common SAS Tasks Bruce F. Gilsen source 11
SESUG 2016 The HPSUMMARY Procedure: A Younger (and Brawnier) Cousin to an Old SAS Friend Anh P. Kellermann,
Jeffrey D. Kromrey		 source 9
PHUSE EU 2016 DIY: Create Your Own SDTM Mapping Framework Bas van Bakel source
presentation source		 11
PHUSE EU 2016 How Well Can you Speak SAS or is What you See What you Get? Bahatska Yuliia source 7
SGF 2016 The HPSUMMARY Procedure: An Old Friend's Younger (and Brawnier) Cousin Anh P. Kellermann,
Jeffrey D. Kromrey		 source
presentation		 9
SGF 2016 Transformers: Revenge of the PROCs Faron Kincheloe source 11
MWSUG 2015 Plotting LSMEANS and Differences in Generalized Linear Models with GTL Robin High 9
MWSUG 2015 Using SAS for the Longitudinal Analysis of Difference Scores Brandy R. Sinco,
Edith Kieffer,
Michael S. Spencer,
Gloria Palmisano,
Gretchen Piatt,
Michele Heisler		 14
SESUG 2015 Having a Mean Headache on Summary Data? Using SAS to Compute Actual Data from Summary Data William 'Gui' Zupko II source 4
SESUG 2015 How to DoW Paul M. Dorfman source 12
WUSS 2015 ODS Output Data Sets That Work for You Stuart D. Long,
Edward Heaton,
Daniel R. Scharf		 source 29
WUSS 2015 Understanding the SAS DATA Step and the Program Data Vector Steven J. First source 14
PharmaSUG CN 2015 Effectively Utilizing Loops and Arrays in the DATA Step Arthur X. Li 17
PharmaSUG 2015 Confidence Intervals Are a Programmer's Friend Xinxin Guo,
Zhaohui Su		 source 8
PharmaSUG 2015 I/O, I/O, It's Off To Work We Go: Digging Into the ATTRC Function Karleen Beaver source 7
PharmaSUG 2015 Inside the DATA Step: Pearls of Wisdom for the Novice SAS Programmer Joshua M. Horstman,
Britney D. Gilbert		 source 11
SGF 2015 Data Summarization for a Dissertation: A Grad Student How-To Paper Elisa L. Priest,
Ashley Collinsworth		 source 8
SGF 2015 Forest Plotting Analysis Macro %FORESTPLOT Jeffrey P. Meyers,
Qian Shi		 source 18
SGF 2015 How Best to Effectively Teach the SAS Language Arthur X. Li source 13
SGF 2015 Inside the DATA Step: Pearls of Wisdom for the Novice SAS Programmer Joshua M. Horstman,
Britney D. Gilbert		 source 11
SESUG 2014 The DoW-Loop Paul M. Dorfman,
Lessia S. Shajenko		 source 12
MWSUG 2014 Ignorance is Not Bliss: Pearls of Wisdom for the Novice SAS Programmer Joshua M. Horstman,
Britney D. Gilbert		 9
MWSUG 2014 Understanding How the DATA Step Works Arthur X. Li 13
WUSS 2014 Quick Tips on Powerful use of Arrays Rahul Pillay source 8
PharmaSUG 2014 Challenges of Processing Questionnaire Data from Collection to SDTM to ADaM and Solutions Using SAS Karin LaPann,
Terek J. Peterson		 source 20
SGF 2014 Challenges of Processing Questionnaire Data from Collection to SDTM to ADaM and Solutions Using SAS Karin LaPann,
Terek J. Peterson		 source 19
SGF 2014 Effectively Utilizing Loops and Arrays in the DATA Step Arthur X. Li source 17
SGF 2014 Nitty Gritty Data Set Attributes Diane Olson source 11
WUSS 2013 How Best to Write a Loop in the DATA Step Arthur X. Li source 19
WUSS 2013 The Essence of DATA Step Programming Arthur X. Li source 19
WUSS 2013 The Many Ways to Effectively Utilize Array Processing Arthur X. Li source 14
SESUG 2013 HOW to DOW Paul M. Dorfman source 12
SESUG 2013 Tailoring Proc Summary for More Efficient Summarizations Bill Parman source 8
MWSUG 2013 Effectively Utilizing Loops and Arrays in the DATA Step Arthur X. Li 17
MWSUG 2013 The Essence of DATA Step Programming Arthur X. Li 19
NESUG 2013 OUT= Is on the Way Out - Use ODS OUTPUT Instead Stanley E. Fogleman 4
NESUG 2013 Using SAS Metadata as a Key Performance Indicator! Vincent J. Amoruccio 11
PharmaSUG 2013 Atypical Applications of the UPDATE Statement John Henry King source 5
PharmaSUG 2013 Effectively Utilizing Loops and Arrays in the DATA Step Arthur X. Li source 17
PharmaSUG 2013 Essentials of PDV: Directing the Aim to Understanding the DATA Step! Arthur X. Li source 12
SGF 2013 Essentials of the Program Data Vector (PDV): Directing the Aim to Understanding the DATA Step Arthur X. Li source 12
SGF 2013 FREQ Out - Exploring Your Data the Old School Way Stephanie R. Thompson source 13
SGF 2013 Know Thy Data: Techniques for Data Exploration Andrew T. Kuligowski,
Charu Shankar		 source 19
SGF 2013 OUT= Is on the Way Out - Use ODS OUTPUT Instead Stanley E. Fogleman source 4
SGF 2013 The Magnificent DO Paul M. Dorfman source 15
NESUG 2012 Long-to-Wide: PROC TRANSPOSE vs Arrays vs PROC SUMMARY Michael S. Zdeb 14
SESUG 2012 A SAS Programming Framework for Data Extraction Using Perl Regular Expression: The First Wave Jiangtang Hu source 10
SESUG 2012 FREQ Out - Exploring Your Data the Old School Way Stephanie R. Thompson source 13
SESUG 2012 Multiple Imputation for Ordinal Variables: A Comparison of SUDAAN's PROC IMPUTE vs. PROC MI Multiple Imputation source 12
SESUG 2012 ODS Output Data Sets That Work for You Stuart D. Long,
Edward Heaton,
Daniel R. Scharf		 source 29
SESUG 2012 Proc Summary Options Beyond The Basics Susmita Pattnaik source 11
SESUG 2012 Through the DoW-Loop, One Statement at a Time Paul M. Dorfman source 12
MWSUG 2012 Effectively Utilizing Loops and Arrays in the DATA Step Arthur X. Li 17
WUSS 2012 OUT= Is on the Way Out - Use ODS OUTPUT Instead Stanley E. Fogleman source 4
WUSS 2012 SAS Programming Basics: Getting Your Data In and Understanding the Data Step Helen D. Carey source 13
PharmaSUG 2012 The Greatest Hits: ODS Essentials Every User Should Know Cynthia L. Zender source 34
SGF 2012 HOW to DOW Paul M. Dorfman,
Lessia S. Shajenko		 source 12
SGF 2012 Solve the SAS ODS Data Trap in PROC MEANS Peter Crawford,
Myra A. Oltsik		 source 12
SGF 2012 The DOW Loop: A Smarter Approach to Your Existing Code Fuad J. Foty source 12
SCSUG 2011 The Greatest Hits: ODS Essentials Every User Should Know Cynthia L. Zender source 34
SESUG 2011 In Lockstep with the DoW-Loop Paul M. Dorfman,
Lessia S. Shajenko		 source 18
WUSS 2011 Quick ODS OUTPUT Statements Patrick Thornton source 3
WUSS 2011 Tips and Techniques for the SAS Programmer Helen D. Carey source 19
MWSUG 2011 Using a Double DOW Loop to Compute Progression Free Survival Matthew Nizol 9
MWSUG 2011 Ways of Creating Macro Variables Kelley Weston 8
NESUG 2011 Choosing ODS Styles: How to Enter your Data in a SAS Fashion Show Gwen Babcock 6
NESUG 2011 Don't Lose Your Data! Tracking and Reporting on Dropped Records Quentin McMullen,
Joshua Black		 9
NESUG 2011 The Greatest Hits: ODS Essentials Every User Should Know Cynthia L. Zender 34
PharmaSUG 2011 The Many Ways to Effectively Utilize Array Processing Arthur X. Li source 14
SGF 2011 Logit Models in Practice: B, C, E, G, M, N, O, ... Joseph C. Gardiner,
Zhehui Luo		 source 20
SGF 2011 Macros for Managing Messy Data: Handling Duplicate Study Participants, and Making Fuzzy Matches Across Multiple Data Sets Jefferson L. Wood,
Dennis G. Fisher,
Lucy Napper,
Grace L. Reynolds		 source 10
SGF 2011 ODS Output Data Sets That Work for You Stuart D. Long,
Edward Heaton,
Daniel R. Scharf		 source 29
SGF 2011 The Essence of DATA Step Programming Arthur X. Li source 19
SGF 2011 The Greatest Hits: ODS Essentials Every User Should Know Cynthia L. Zender source
zip		 34
SGF 2011 The Many Ways to Effectively Utilize Array Processing Arthur X. Li source 14
NESUG 2010 HOW to DOW Paul M. Dorfman 18
SCSUG 2010 Take Control: Understanding and Controlling Your Do-Loops Sarah Woodruff,
Toby Dunn		 source 21
WUSS 2010 Get a Grip on Arrays in Just 50 Minutes! Arthur X. Li source 14
WUSS 2010 Macros for Managing Messy Data: Handling Duplicate Study Participants, and Making Fuzzy Matches Across Multiple Data Sets Jefferson L. Wood,
Dennis G. Fisher,
Lucy Napper,
Grace L. Reynolds		 source 10
WUSS 2010 Tips for Constructing a Data Warehouse Part 2 Curtis A. Smith source 11
MWSUG 2010 Exploring, Analyzing, and Summarizing Your Data: Choosing and Using the Right SAS Tool from a Rich Portfolio Douglas Thompson 25
MWSUG 2010 Understanding the SAS DATA Step and the Program Data Vector Steven J. First 14
MWSUG 2010 Using HPMIXED and Other SAS Procedures to Efficiently Analyze Large Dimension Registry Data Matthew Fenchel,
Gary McPhail,
Rhonda D. VanDyke		 19
MWSUG 2010 Ways of Creating a Macro Variable Kelley Weston 8
SESUG 2010 Take Control: Understanding and Controlling Your Do-Loops Sarah Woodruff source 21
SESUG 2010 The DOW-Loop Unrolled Paul M. Dorfman source 15
SESUG 2010 The MEANS/SUMMARY Procedure: Getting Started Arthur L. Carpenter source 10
SGF 2010 Get the Scoop on the Loop: How Best to Write a Loop in the DATA Step Arthur X. Li source 19
SGF 2010 The MEANS/SUMMARY Procedure: Doing More Arthur L. Carpenter source 14
SGF 2010 The MEANS/SUMMARY Procedure: Getting Started Arthur L. Carpenter source 10
SGF 2010 Transposing Data Using the IDGROUP Option in PROC SUMMARY John Henry King,
Michael S. Zdeb		 source 6
MWSUG 2009 Group Sequential Analysis Using the New SEQDESIGN and SEQTEST Procedures Yang Yuan 20
PNWSUG 2009 The MEANS/SUMMARY Procedure: Getting Started and Doing More Arthur L. Carpenter 19
NESUG 2009 The DOW-Loop Unrolled Paul M. Dorfman,
Marina Fridman		 18
WUSS 2009 Don't Be Loopy: Re-Sampling and Simulation the SAS Way David L. Cassell source 18
WUSS 2009 The Fundamentals of Data Step Programming I: The Essence of Data Step Programming and By-Group Processing Arthur X. Li source 20
WUSS 2009 The Fundamentals of DATA Step Programming II: Looping Arthur X. Li source 13
PharmaSUG 2009 Don't Be Loopy: Re-Sampling and Simulation the SAS Way David L. Cassell 18
PharmaSUG 2009 Image is Almost Everything: Displaying Statistics Via ODS R. Scott Leslie 8
PharmaSUG 2009 Presenting Descriptive Statistics by the Rapid Processing of Data Sets from Proc Means Rod Norman 4
PharmaSUG 2009 Sweet Smell of SucSAS - When Your DATA Step Does What is Intended!! Arthur X. Li 19
PharmaSUG 2009 The MEANS/SUMMARY Procedure: Doing More Arthur L. Carpenter 14
PharmaSUG 2009 Transposing Data Using PROC SUMMARY'S IDGROUP Option John Henry King,
Mount Ida		 6
PharmaSUG 2009 TT05 The MEANS/SUMMARY Procedure Arthur L. Carpenter 10
SGF 2009 Easier Exploratory Analysis for Epidemiology: A Grad Student "How-To" Paper Elisa L. Priest,
Brian Adams,
Lori A. Fischbach		 source 11
SGF 2009 Group Sequential Analysis Using the New SEQDESIGN and SEQTEST Procedures Yang Yuan source 20
SGF 2009 Image is Almost Everything: Displaying Statistics Via ODS R. Scott Leslie source 8
SGF 2009 The DOW-Loop Unrolled Paul M. Dorfman,
Koen Vyverman		 source 18
SGF 2009 Understanding the SAS DATA Step and the Program Data Vector Steven J. First source 16
WUSS 2008 Image is Almost Everything: Displaying Statistics Via ODS R. Scott Leslie source 5
WUSS 2008 Surviving Left Truncation Using PROC PHREG Aimee Foreman,
Ginny Lai,
Dave P. Miller		 source 8
WUSS 2008 The Essence of DATA Step Programming Arthur X. Li source 19
WUSS 2008 The MEANS/SUMMARY Procedure: Getting Started and Doing More Arthur L. Carpenter source 19
WUSS 2008 The Power of the BY Statement Toby Dunn,
Paul A. Choate		 source 16
SESUG 2008 SET, MERGE and beyond. Erik W. Tilanus source 15
SESUG 2008 The DOW-Loop Unrolled Paul M. Dorfman,
Lessia S. Shajenko		 source 19
NESUG 2008 The DOW-Loop Unrolled Paul M. Dorfman 18
PharmaSUG 2008 The DOW-Loop Unrolled Paul M. Dorfman,
Lessia S. Shajenko		 18
SGF 2008 Adventures in ODS: Producing Customized Reports Using Output from Multiple SAS Procedures Stuart D. Long,
Jeffrey M. Abolafia,
Lawrence Park		 source 23
SGF 2008 Any WAY you Want it: Getting the Right TYPEs of Observations Out of PROC SUMMARY or MEANS Christianna S. Williams source 8
SGF 2008 ODS and Output Data Sets: What You Need to Know Myra A. Oltsik source 13
SGF 2008 SET, MERGE and beyond. Erik W. Tilanus source 15
SGF 2008 Steps to Success with the SAS Output Delivery System Andrew H. Karp source 15
SGF 2008 Using DO Statements, Links, and Arrays Jimmy A. DeFoor source 13
NESUG 2007 Common Pitfalls in SAS Statistical Analysis Macros in a Mass Production Environment Huei-Ling Chen,
Aiming Yang		 9
NESUG 2007 The Program Data Vector As an Aid to DATA step Reasoning Marianne L. Whitlock 13
NESUG 2007 Using SAS ODS to Extract and Merge Statistics from Multiple SAS Procedures into a Single Summary Report, a Detailed Methodology Stuart D. Long,
Jeffrey M. Abolafia,
Lawrence Park		 22
SESUG 2007 The DOW-Loop Unrolled Paul M. Dorfman,
Lessia S. Shajenko		 source 18
WUSS 2007 Automated Programming Techniques for the Data Warehouse Manager Renato G. Villacorte source 6
WUSS 2007 Don't Be Loopy: Re-Sampling and Simulation the SAS Way David L. Cassell source 18
WUSS 2007 The Power of the BY Statement Toby Dunn,
Paul A. Choate		 source 16
WUSS 2007 The TRANSPOSE Procedure or How to Turn your Data Around David Fickbohm source 10
WUSS 2007 Writing a "lean and mean" PROC MEANS: CLASS vs. BY and OUTPUT vs. ODS OUTPUT Eric P. Elkin source 3
SCSUG 2007 The Power of the BY Statement Toby Dunn,
Paul A. Choate		 11
SCSUG 2007 Using Links, Arrays, and Do-Loops Jimmy A. DeFoor 13
PNWSUG 2007 Don't Be Loopy: Re-Sampling and Simulation the SAS Way David L. Cassell 18
PNWSUG 2007 Using Links, Arrays, and Do-Loops Jimmy A. DeFoor 13
PharmaSUG 2007 The TRANPOSE Procedure or How to Turn It Around Janet E. Stuelpner 9
PharmaSUG 2007 Using Multiple Output Statements in the Summary Procedure Britney D. Gilbert 3
SGF 2007 Don't Be Loopy: Re-Sampling and Simulation the SAS Way David L. Cassell source 18
SGF 2007 Getting the Most from PROC MEANS Andrew H. Karp source 9
SGF 2007 Parameter Gathering Techniques for Data Driven Programming Renato G. Villacorte source 5
SGF 2007 The Power of the BY Statement Paul A. Dunn,
Toby Choate		 source 16
SGF 2007 Using SAS Macros to Produce Tables for Publication from SAS-Callable SUDAAN Roger P. Pickering source 10
SGF 2007 Using SAS to Process Repeated Measures Data - A Hands-On Approach Terry Gareleck,
Cyndie B. Fain		 source 12
SGF 2007 Variable Screening for Multinomial Logistic Regression on Very Large Data Sets as Applied to Direct Response Modeling John A. Cherrie source 12
PHUSE EU 2006 Adding (p-) Value to Tables -- a Programmer''s Perspective Kathryn Wright source 10
SESUG 2006 Using SAS ODS to Extract and Merge Statistics from Multiple SAS Procedures into a Single Summary Report, a Detailed Methodology Stuart D. Long source 21
WUSS 2006 Parameter Gathering Techniques for Data Driven Programming Renato G. Villacorte source 5
WUSS 2006 Steps to Success with PROC MEANS Andrew H. Karp source 12
WUSS 2006 Tips & Techniques with PROC MEANS Andrew H. Karp source 8
NESUG 2006 Any WAY you Want it: Getting the Right TYPEs of Observations Out of PROC SUMMARY or MEANS Christianna S. Williams 7
NESUG 2006 MIMO: Multiple Inputs Multiple Outputs - Multiplying the Fun while doing the Data Step John Fahey 9
SUGI 2006 Combining the Power of ODS, Data Set Concatenation, and DDE to Output Customized Statistical Results from SAS to Microsoft Excel Navneet K. Dhand,
Jenny-Ann Toribio		 source 10
SUGI 2006 FREQ n' MEANS Marge Scerbo,
Michael S. Lajiness		 source 19
SUGI 2006 Reading Between the Lines: Distinguishing Macro Code from Open Code in Macros Michael J. Molter source 16
SUGI 2006 The TRANSPOSE Procedure or How to Turn It Around Janet E. Stuelpner source 9
SUGI 2006 Using SAS ODS to Extract and Merge Statistics from Multiple SAS Procedures Stuart D. Long,
Jeffrey M. Abolafia,
Lawrence Park		 source 21
SUGI 2006 Using SAS to Process Repeated Measures Data Terry Fain,
Cyndie B. Gareleck		 source 11
SESUG 2005 Manipulating Data: Elements of the DATA Step Language Paul M. Dorfman source 19
SESUG 2005 The Program Data Vector As an Aid to DATA step Reasoning Marianne L. Whitlock source 14
SESUG 2005 Using SAS to Process Repeated Measures Data Terry Fain source 10
WUSS 2005 Tips & Techniques with PROC MEANS Andrew H. Karp source 8
NESUG 2005 Beyond FORMAT Basics Michael S. Zdeb 20
NESUG 2005 Freq n' Means Marge Scerbo,
Michael S. Lajiness		 19
NESUG 2005 HOLY MACRO! An Intuitive Approach to Understanding the Macro Facility Michael J. Molter 20
PharmaSUG 2005 Understanding the Inner Workings of SAS II What to Watch Out for When Using OUTPUT and SORT Yan Lei 5
PharmaSUG 2005 Using Procedure-Based ODS Data Components in Statistical Reporting Vincent J. Faber 10
SUGI 2005 HOLY MACRO! An Intuitive Approach to Understanding the Macro Facility Michael J. Molter source 20
SUGI 2005 Let Your Data Power Your DATA Step: Making Effective Use of the SET, MERGE, UPDATE, and MODIFY Statements Howard L. Schreier source 19
SUGI 2005 Techniques for Effectively Selecting Groups of Variables Stuart Pollack source 4
SUGI 2005 Using Procedure-Based ODS Data Components in Statistical Reporting Vincent J. Faber source 10
SUGI 2005 Using SAS to Process Repeated Measures Data Terry Fain,
Cyndie B. Gareleck		 source 10
SESUG 2004 A Second Look at SAS Macro Design Issues H. Ian Whitlock source 19
SESUG 2004 What's That Note/Warning/Error Mean and How Do I Fix It? Deb Cassidy source 10
WUSS 2004 Getting the Most from PROC MEANS Andrew H. Karp source 8
PNWSUG 2004 ODS Tips and Tricks Lauren E. Haworth 7
SUGI 2004 A Second Look at SAS Macro Design Issues H. Ian Whitlock source 19
SUGI 2004 Advanced Programming Techniques for Working with Color in SAS Software Perry Watts source 19
SUGI 2004 Steps to Success with PROC MEANS Andrew H. Karp source 13
WUSS 2003 Creating Output Data Sets From Almost Any Procedure Using The Output Delivery System Curtis A. Smith source 6
WUSS 2003 Tips and Techniques with PROC MEANS Andrew H. Karp source 8
MWSUG 2003 Tips and Techniques with PROC MEANS Andrew H. Karp 6
NESUG 2003 Advanced Programming Techniques for Working with Color in SAS Software Perry Watts 18
NESUG 2003 Interleaving a Dataset with Itself: How and Why Howard L. Schreier 6
SUGI 2003 New Ways and Means to Summarize Files Curtis A. Smith source 6
MWSUG 2002 Using the FILEVAR= Option for Input and Output Derek P. Morgan 4
SCSUG 2002 The Essential Meaning of PROC MEANS: A Beginner's Guide to Data Summarization and Analysis Using PROC MEANS Andrew H. Karp 10
NESUG 2002 The Essential Meaning of PROC MEANS: A Beginner's Guide to Summarizing Data Using SAS Software Gary M. McQuown,
Andrew H. Karp		 10
SESUG 2002 The Essential Meaning of PROC MEANS: A Beginner's Guide to Summarizing Data Using SAS Software Andrew H. Karp,
Gary M. McQuown		 source 10
SESUG 2002 Using ODS to Capture Statistics from PROC GLM Frank L. Roediger source 6
WUSS 2002 New Ways and Means to Summarize Files Curtis A. Smith source 6
SUGI 2002 Advanced Tips and Techniques with PROC MEANS Andrew H. Karp source 7
SUGI 2002 Using the FILEVAR= Option for Input and Output Derek P. Morgan source 4
MWSUG 2001 The Essential Meaning of PROC MEANS: A Beginner's Guide to Data Summarization Using the SAS System Andrew H. Karp 10
WUSS 2001 Changes and Enhancements to PROCs MEANS and SUMMARY in Version 8 of the SAS System Andrew H. Karp source 6
WUSS 2001 ODS Tips and Tricks Lauren E. Haworth source 7
SESUG 2001 Changes and Enhancements to PROC MEANS In Version 8 of the SAS System Andrew H. Karp source 6
SESUG 2001 Manipulating Data: Elements of the DATA Step Language Paul M. Dorfman source 10
SESUG 2001 ODS, YES! Odious, NO! - An Introduction to the SAS Output Delivery System Lara K. Bryant,
Sally M. Muller,
Ray Pass		 source 10
SESUG 2001 Using Functions and Arrays in the SAS System to Manage and Manipulate Data Ben Cochran source 6
SCSUG 2001 Changes and Enhancements to PROC MEANS In Version 8 of the SAS System Andrew H. Karp 6
SCSUG 2001 ODS, YES! Odious, NO! - An Introduction to the SAS Output Delivery System Lara K. Bryant,
Sally M. Muller,
Ray Pass		 10
SCSUG 2001 Using Functions and Arrays in the SAS System to Manage and Manipulate Data Ben Cochran 6
PharmaSUG 2001 Using Functions and Arrays in the SAS System to Manage and Manipulate Data Ben Cochran 6
SUGI 2001 ODS, YES! Odious, NO! - An Introduction to the SAS Output Delivery System Lara K. Bryant,
Ray Pass,
Sally M. Muller		 source 10
SUGI 2001 The Essential Meaning of PROC MEANS: A Beginner's Guide to Summarizing Data in SAS Andrew H. Karp source 10
NESUG 2000 ODS, YES! Odious, NO! - An Introduction to the SAS Output Delivery System Lara K. Bryant,
Sally M. Muller,
Ray Pass		 10
NESUG 2000 PROC MEANSTM: More than just your average procedure Peter R. Welbrock 10
WUSS 2000 Detecting Curvillnear Relationships in PROC REG Mel Widawski source 9
WUSS 2000 SAS STAT applications in Econometrics Mathura Thillainathan,
George C. J. Fernandez		 source 10
SUGI 2000 Detecting Curvilinear Relationships in PROC REG Mel Widawski source 9
SUGI 2000 PROC MEANS: More Than Just Your Average Procedure Peter R. Welbrock source 10
WUSS 1999 An Everyday Guide to Versions 7 and 8 of the SAS System Susan J. Slaughter,
Lora D. Delwiche		 source 10
SUGI 1999 An Introduction to PROC LOESS for Local Regression Robert A. Cohen source 9
NESUG 1998 Risk Evaluation after Heart Valve Replacement by PROC PHREG Choa Chen 7
SESUG 1998 The Program Data Vector As an Aid to DATA step Reasoning Marianne L. Whitlock 10
PNWSUG 1998 Do Loops in SAS Software Dana Rafiee 11
SUGI 1998 New V7 Client/Server Capabilities to Solve and Secure Your Distributed Processing Needs Cheryl A. Garner source 10
SESUG 1997 CAUTIONARY TALES FOR SAS PROGRAMMERS (or, Coding Pitfalls for the Unwary) Jeny Le Breton 7
SCSUG 1996 SAS System Programming Tips and Efficiencies: A Tutorial Andrew H. Karp 8
NESUG 1996 Reading Hiearchical Files Larry Gertzog 6
WUSS 1996 SAS System Programming Tips and Efficiencies: A Tutorial Andrew H. Karp source 8
SEUGI 1996 Controlling looping code structures John R. Whittington source 3
SUGI 1996 SUM Enchanted Procedure: The Advanced Power of PROC SUMMARY David E. Beam source 6
NESUG 1995 PROC SUMMARY: A Powerful Exploratory Data Analysis Tool Kim L. Kolbe Ritzow 10
WUSS 1994 Your Program Works, But is it Efficient? Sheree H. Anderson source 3
SUGI 1993 DATA Step Changes and Enhancements Jeffrey A. Polzin source 6
SESUG 1993 Combined Ratio Estimates Computed with SAS Joan M. Pausche 6
SCSUG 1992 The SAS System Supervisor - A Version 6 Update Merry G. Rabb,
Donald J. Henderson,
Jeffrey A. Polzin		 8
NESUG 1992 SAS System Supervison - A Version 6 Update Merry G. Rabb,
Donald J. Henderson,
Jeffrey Polzin		 8
MWSUG 1992 DATA Step Changes and Enhancements Jeffrey A. Polzin 6
SEUGI 1992 DATA Step Changes and Enhancements Bent Sorenson source 6
SUGI 1992 The SAS System Supervisor - A Version 6 Update Merry G. Rabb,
Donald J. Henderson,
Jeffrey A. Polzin		 source 8
SEUGI 1991 Some New Features in the DATA STEP Sarah Bell source 7
SUGI 1991 A Comparison of DATA Step Performances in Releases 6.06 and 5.18 Jimmy A. DeFoor source 6
SUGI 1991 An Insider's Sneak Preview of the Next DATA Step Release Jeffrey A. Polzin source 7
SUGI 1991 The SAS System Supervisor - A Version 6 Update Donald J. Henderson,
Merry G. Rabb,
Jeffrey A. Polzin		 source
NESUG 1990 The SAS Supervisor - A Version 6 Update Donald J. Henderson,
Merry G. Rabb,
Jeffrey A. Polzin		 11
MWSUG 1990 The SAS Supervisor - A Version 6 Update Donald J. Henderson,
Merry G. Rabb,
Jeffrey A. Polzin		 10
SUGI 1990 The SAS Supervisor - A Version 6 Update Donald J. Henderson,
Merry G. Rabb,
Jeffrey A. Polzin		 source 9
SUGI 1990 Working with the SUMMARY Procedure: An Introduction John S. Boyden source 6
SUGI 1989 The SAS Supervisor and SET/MERGE Processing Aiman M. Zeid source 10
NESUG 1988 The SAS Supervisor Donald J. Henderson,
Merry G. Rabb		 pdf 16
SUGI 1988 Data Entry in a Clinical Trial Using Windows in the SAS System for Personal Computers MaryAnne DePesquo Hope source 4
SUGI 1988 The SAS Supervisor Donald J. Henderson,
Merry G. Rabb		 source 7
SUGI 1987 The SAS Supervisor Donald J. Henderson,
Merry G. Rabb		 source 10
SEUGI 1985 MXG Version 2 Jim Thomason source 2
SUGI 1984 On Generating Statistics, Formatting Results and Efficiency Ingrid A. Amara,
Gary G. Koch		 source 6
SUGI 1984 PROC JACKREG-A SAS Procedure for Jackknife Regression Daniel M. Chilko,
Panayiotis Hambi,
Gerald R. Hobbs		 source 6
SUGI 1983 PROC DISCRETE-A Procedure for Fitting Discrete Probability Distributions Charles E. Gates,
James P. Geaghan,
George D. Williams		 source 4
SUGI 1982 An Integration of System 2000 and Statistical Analysis System (SAS) Roger E. Booker source 7
SUGI 1982 Cartographic Evaluation of Environmental Management Strategies Karen L. Daniels,
Michael P. Farrell,
Jonathan C. Goyert,
Rodney H. Strand		 source
SUGI 1978 Capabilities of SAS as a Clinical Research Data Management and Analysis System Frank E. Harrell Jr. source 4
SUGI 1978 Repeated Measures in SAS John A. Courtright source 5

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