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164 papers; 134 titles.

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Conference × Year × Title × Authors Extras Pages
PharmaSUG 2026 Do One Task, Get Another Done for Free: Use DEFX Tags in Comments to Fill Out Your define.xml Brendan Bartley,
Megan Hinger		 source 21
PharmaSUG 2026 SAS and R for Expanding Data for Pharmacometrics Analysis (PMx) Analysis Data Sets Jeffrey Rathbun,
Rebecca Humphrey		 source 8
MWSUG 2025 Last Observation Carried Forward (LOCF) in Longitudinal Clinical Studies: Adopting a Functional Approach to Imputing Missing Values Using PROC FCMP, the SAS Function Compiler Troy Martin Hughes source 9
SESUG 2025 Last Observation Carried Forward (LOCF) in Longitudinal Pharmaceutical and Clinical Trials Studies: Adopting a Functional Approach to Imputing Missing Values Using PROC FCMP, the SAS Function Compiler Troy Martin Hughes 9
WUSS 2025 Last Observation Carried Forward (LOCF) in Longitudinal Clinical Studies: Adopting a Functional Approach to Imputing Missing Values Using PROC FCMP, the SAS Function Compiler Troy Martin Hughes source 9
PharmaSUG 2025 Last Observation Carried Forward (LOCF) in Longitudinal Patient Studies: A Functional Approach to Imputing Missing Values Using PROC FCMP, the SAS Function Compiler Troy Martin Hughes source 9
WUSS 2024 Count, Lag, Retain! Let's go through it one more time! Steven C. Black source 10
PharmaSUG 2021 Programming Time Varying Concomitant Medication Covariates in NONMEM PopPK Dataset Dan Xiao,
Jing Su,
Shuqi Zhao,
Xiang Liu		 source 11
PharmaSUG 2020 How to Achieve More with Less Code Timothy J. Harrington source 13
SESUG 2019 Cutting Out the Middle Man - Bypassing ADaM to Calculate Tumor Response Inputs using RECIST 1.1 Guidelines and Collected Data in SDTM Format Response Inputs source 6
WUSS 2019 Order, Order! Four Ways to Reorder Your Variables, Ranked by Elegance and Efficiency Louise S. Hadden source 20
WUSS 2019 Tips for the lazy typist (and other strategies for smart coding) Melissa R. Pfeiffer source 10
SCSUG 2018 Tips for the lazy typist (and other strategies for smart coding) Melissa R. Pfeiffer source 9
WUSS 2018 Bring the Vampire out of the Shadows: Understanding the RETAIN and COUNT functions in SAS Steven C. Black source 8
WUSS 2018 The Inevitable Use of RETAIN Statement in Multiple Scenarios with Examples for Creating Efficacy Parameters Prabhakara Rao Burma,
Venkata N Madhira		 source 5
PharmaSUG 2018 Discover the Deeper DATA Step Timothy J. Harrington source 14
SESUG 2017 RETAINing Your Sanity: 5 Ideas to Manipulate Data Using the RETAIN Statement Matthew Taylor source 7
PharmaSUG 2017 Power of Interleaving and RETAIN Combination in Data Manipulation Zongming Pan source 10
SGF 2017 Know Your Tools Before You Use Justin Jia source 16
SESUG 2015 Because We Can: Using SAS System Tools to Help Our Less Fortunate Brethren Fortunate Brethren source 9
SESUG 2015 The Mystery of Automatic Retain in a SAS Data Step Huei-Ling Chen source 8
PharmaSUG 2015 Inside the DATA Step: Pearls of Wisdom for the Novice SAS Programmer Joshua M. Horstman,
Britney D. Gilbert		 source 11
PharmaSUG 2015 The Path To Treatment Pathways Tracee Vinson-Sorrentino source 6
SGF 2015 Examination of Three SAS Tools for Solving a Complicated Data Summary Problem Carry W. Croghan source 12
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
MWSUG 2014 How Do I ...? Some Beginners FAQs Peter W. Eberhardt,
Audrey Yeo		 11
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
PharmaSUG 2014 Swimmer Plot: Tell a Graphical Story of Your Time to Response Data Using PROC SGPLOT Stacey D. Phillips source 12
PharmaSUG 2014 Understanding and Applying the Logic of the DOW-Loop Arthur X. Li source 12
SGF 2014 Ordering Columns in a SAS Data Set: Should You Really RETAIN That? Andrew W. Clapson source 3
SGF 2014 Understanding and Applying the Logic of the DOW-Loop Arthur X. Li source 12
WUSS 2013 The Essence of DATA Step Programming Arthur X. Li source 19
MWSUG 2013 The Essence of DATA Step Programming Arthur X. Li 19
PharmaSUG 2013 Essentials of PDV: Directing the Aim to Understanding the DATA Step! Arthur X. Li source 12
PharmaSUG 2013 Let's get SASsy Amie Bissonett source 6
SGF 2013 Essentials of the Program Data Vector (PDV): Directing the Aim to Understanding the DATA Step Arthur X. Li source 12
SGF 2013 Reordering Columns after PROC TRANSPOSE (or Anytime You Want, Really) Sau Yiu source 4
SGF 2013 SAS Data Management Techniques: Cleaning and Transforming Data for Delivery of Analytic Data Sets Christopher W. Schacherer source 38
NESUG 2012 Combining Continuous Events and Calculating Duration in Kaplan-Meier Analysis Using a Single DATA Step Hui Song,
George Laskaris		 8
SCSUG 2012 SAS Data Management Techniques: Cleaning and Transforming Data for Delivery of Analytic Data Sets Christopher W. Schacherer source 38
SESUG 2012 Manage Hierarchical or Associated Data with the RETAIN Statement Alan R. Mann,
Harpers Ferry		 source 5
MWSUG 2012 SAS Data Management Techniques: Cleaning and Transforming Data for Delivery of Analytic Data Sets Christopher W. Schacherer 38
WUSS 2012 SAS Programming Basics: Getting Your Data In and Understanding the Data Step Helen D. Carey source 13
PharmaSUG 2012 Calculating time-to-event parameters using a single DATA step and a RETAIN statement Andrew L Hulme source 7
PharmaSUG 2012 The Use and Abuse of the Program Data Vector James R. Johnson source 23
SGF 2012 The FILENAME Statement: Interacting with the World Outside of SAS Christopher W. Schacherer source 29
SGF 2012 The Use and Abuse of the Program Data Vector James R. Johnson source 23
SCSUG 2011 Intro to Longitudinal Data: A Grad Student "How-To" Paper Elisa L. Priest source 14
SESUG 2011 Identifying, Tracking, and Analyzing Patterns in Finite Concurrent and Sequential Events using SAS Vijayalakshmi Sampath source 10
MWSUG 2011 Taming the Interactive SAS Environment: Tips and Tricks for VIEWTABLE, The Enhanced Editor and More Roger D. Muller,
Joshua M. Horstman		 12
PharmaSUG 2011 Quick - Ready Set Retain, and Maybe Reset! Lisa Fine source 8
SGF 2011 Longitudinal Data Techniques: Looking Across Observations Ronald P. Cody source 7
SGF 2011 Ready, Set, Retain, and then Maybe Reset Lisa Fine source 11
SGF 2011 The Essence of DATA Step Programming Arthur X. Li source 19
NESUG 2010 Automatically Converting Character Variables That Store Numbers to Numeric Variables Christopher J. Bost 13
NESUG 2010 How to Think Through the SAS DATA Step H. Ian Whitlock 17
NESUG 2010 Please Don't Lag Behind LAG ! Anjan Matlapudi,
James D. Knapp		 12
WUSS 2010 Creating Variables: Traps and Pitfalls Olena Galligan source 10
WUSS 2010 LOCF-Different Approaches, Same Results Using LAG Function, RETAIN Statement, and ARRAY Facility Iuliana Barbalau source 5
WUSS 2010 Longitudinal Data Techniques: Looking Across Observations Ronald P. Cody source 7
WUSS 2010 Use RETAIN Statement and LAG Function to Indentify Consecutively Repeated Conditions Lan Xiao source 5
SGF 2010 Faster Results by Multi-threading DATA Steps Ian J. Ghent source 7
SGF 2010 SAS State of Mind: A Guide to Learning SAS for the Stata User Sarah J. Beck source 9
SGF 2010 Tales from the Help Desk 4: Still More Solutions for Common SAS Mistakes Bruce F. Gilsen source 8
SCSUG 2009 Working with Longitudinal Data Ronald P. Cody 4
MWSUG 2009 Effective Use of RETAIN Statement in SAS Programming Yi Zhao 4
WUSS 2009 If I Only Had a Map. Getting from Here to There: Common Approaches to Solving Data Step Logic Issues Kim M. Wilson source 17
WUSS 2009 The Fundamentals of Data Step Programming I: The Essence of Data Step Programming and By-Group Processing Arthur X. Li source 20
PharmaSUG 2009 Sweet Smell of SucSAS - When Your DATA Step Does What is Intended!! Arthur X. Li 19
SGF 2009 If I Only Had a Map. Getting from Here to There: Common Approaches to Solving Data Step Logic Issues Kim M. Wilson source 17
SGF 2009 You Need to Consolidate Massive Amounts of Data? Select the Fastest Method or Go for Minimal Memory Requirements to Build Your Result Henri Theuwissen source 14
WUSS 2008 E Pluribus Unum: How to Obtain One Observation from Multiple Observations by Limiting, Reshaping, and Summarizing Data Eric P. Elkin source 13
WUSS 2008 The Essence of DATA Step Programming Arthur X. Li source 19
SESUG 2008 The Art of Debugging H. Ian Whitlock source 20
NESUG 2008 Tales from the Help Desk 4: Still More Solutions for Common SAS Mistakes Bruce F. Gilsen 8
SGF 2008 The Art of Debugging H. Ian Whitlock source 20
NESUG 2007 Because We Can: Using SAS System Tools to Help Our Less Fortunate Brethren John J. Cohen 9
NESUG 2007 Metadata 101: A Beginner's Guide to Table-Driven Applications Programming Frank C. DiIorio 11
NESUG 2007 Summing with SAS Tatiana Homonoff 12
NESUG 2007 The Program Data Vector As an Aid to DATA step Reasoning Marianne L. Whitlock 13
SESUG 2007 Smart SAS Tricks Monal Kohli,
Smith Hanley		 source 7
WUSS 2007 A Datum to Remember: Using the RETAIN Statement Jeanina M. Worden,
Chunmei Yang		 source 10
WUSS 2007 Analyzing Multiple Records Per Subject with BY-Group Processing and RETAIN. Easier than You Think . . . Carter Sevick source 8
WUSS 2007 Data Driven Annotations: An Introduction to SAS/GRAPH's Annotate Facility Arthur L. Carpenter source 17
WUSS 2007 Data Driven Annotations: An Introduction to SAS/GRAPH's Annotate Facility Arthur L. Carpenter source 17
SGF 2007 How to Think Through the SAS DATA Step H. Ian Whitlock source 19
SGF 2007 Using SAS to Process Repeated Measures Data - A Hands-On Approach Terry Gareleck,
Cyndie B. Fain		 source 12
PHUSE EU 2006 The Power of RETAIN Statement in Clinical Trial Programming by Examples Baoxian Lan source 5
SESUG 2006 How to Think Through the SAS DATA Step H. Ian Whitlock source 20
WUSS 2006 Data Driven Annotations: An Introduction to SAS/GRAPH's Annotate Facility Arthur L. Carpenter source 17
PharmaSUG 2006 Data Driven Annotations: An Introduction to SAS/GRAPH's Annotate Facility Arthur L. Carpenter 17
SUGI 2006 Data-Driven Annotations: An Introduction to the SAS/GRAPH Annotate Facility Arthur L. Carpenter source 17
SUGI 2006 How to Think Through the SAS DATA Step H. Ian Whitlock source 20
SUGI 2006 Using SAS to Process Repeated Measures Data Terry Fain,
Cyndie B. Gareleck		 source 11
SESUG 2005 How SAS Thinks Neil H. Howard 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 SAS Essentials Neil H. Howard source 19
NESUG 2005 "LAG With a WHERE" and Other DATA Step Stories Neil H. Howard 14
NESUG 2005 Beyond FORMAT Basics Michael S. Zdeb 20
NESUG 2005 How SAS Thinks Neil H. Howard 19
PharmaSUG 2005 How SAS Thinks Neil H. Howard 20
PharmaSUG 2005 RETAIN or NOT? Is LAG Far Behind? Venky Chakravarthy 9
PharmaSUG 2005 Retaining, Lagging, Leading, and Interleaving Data Toby Dunn,
Chang Y. Chung		 8
PharmaSUG 2005 Speed up your SAS Programs Karthikeyan Chidambaram 5
SUGI 2005 Using SAS to Process Repeated Measures Data Terry Fain,
Cyndie B. Gareleck		 source 10
NESUG 2004 How SAS Thinks or Why the DATA Step Does What It Does Neil H. Howard 19
SCSUG 2004 Retaining, Lagging, Leading, and Interleaving Data Toby Dunn 14
SCSUG 2004 SAS as a Multi-Purpose Tool in the Healthcare Environment Robert Muzny 7
SESUG 2004 Why the DATA Step Does What It Does Neil H. Howard source 19
WUSS 2004 Speed up your SAS Programs Karthikeyan Chidambaram source 5
PharmaSUG 2004 "LAG With a WHERE" and Other DATA Step Stories Neil H. Howard 14
PharmaSUG 2004 How SAS Thinks or Why the DATA Step Does What It Does Neil H. Howard 17
SUGI 2004 How SAS Thinks or Why the DATA Step Does What It Does Neil H. Howard source 19
SUGI 2004 SAS Data Quality - Cleanse: Techniques for Merge/Purge on Very Large Datasets Michael Krumenaker,
George Bukhbinder,
Xiaoyan Yang		 source 9
WUSS 2003 Overlapping Date Segments: How to Clean Up the Mess Doug Shannon,
Wade Bannister		 source 2
SCSUG 2003 FUZZY MERGES: Examples and Techniques Malachy J. Foley 10
SESUG 2003 Getting What You Want Out of a Many-to-Many Merge Sonal Pathak source 5
MWSUG 2003 Getting More For Less: A Few SAS Programming Efficiency Issues Arthur L. Carpenter 7
NESUG 2003 Streamlining Complex Data Merges Using the RETAIN Statement Rebecca Goldblatt,
Irv Gutin		 2
PharmaSUG 2003 The Use and Abuse of the Program Data Vector Jim Johnson 10
SUGI 2003 RETAINing Information to Identify Entity Characteristics John D. Chapman source 3
SCSUG 2002 Selecting Records and Assigning Attributes Jimmy A. DeFoor 8
NESUG 2002 Get With the Validation Program - Successful Steps to Edit Check Failures Michael Rea 2
NESUG 2002 Longitudinal Data Techniques: Looking Across Observations Ronald P. Cody 6
SESUG 2002 DATA Step Essentials Neil H. Howard source 10
SESUG 2002 Reordering Variables in a SAS Data Set Imelda C. Go source 3
SUGI 2002 Longitudinal Data Techniques: Looking Across Observations Ronald P. Cody source 4
SUGI 2002 SPAN SPAN AWAY! Creating One Unique Record for Overlapping Admissions and Discharges from Multiple Inpatient Hospital Stays Shabnam Mehra,
Robyn Spittle,
Becky Larsen,
Diane Haynes,
Kathy Dailey		 source 3
SESUG 2001 Using the SAS Annotate Facility for Creating Custom Graphs Patrick M. McGown source 8
SCSUG 2001 Using the SAS Annote Facility for Creating Custom Graphs Patrick M. McGown 8
SESUG 2000 SAS Programming and HEDIS: An Introductory Overview Christopher Plummer source 9
NESUG 2000 Avoiding Mayhem in the New Millennium: Working with Missing Data JoAnn R. Matthews 10
NESUG 2000 Longitudinal Data Techniques: Looking Across Observations Ronald P. Cody 6
SUGI 2000 Avoiding Mayhem in the New Millennium: Working with Missing Data JoAnn R. Matthews source 10
SUGI 2000 Calculating Time Intervals Using RETAIN Denise Gaskins source 2
SCSUG 1999 Longitudinal Data Techniques Ronald P. Cody 6
SESUG 1999 EVERYTHING IN ONE RECORD: CREATING ONE-LINERS WITH MERGES AND RETAINS Sharon W. Stroud source 3
SESUG 1999 FUZZY MERGES: Examples and Techniques Malachy J. Foley source 10
NESUG 1999 Getting More For Less: A Few SAS Programming Efficiency Issues Arthur L. Carpenter 4
NESUG 1999 Longitudinal Data Techniques: Looking Across Observations Ronald P. Cody 6
NESUG 1999 SAS Programming and HEDIS: An Introductory Overview Christopher Plummer 7
NESUG 1999 The RETAIN Statement: One Window into the SAS Data Step Paul Gorrell 6
SUGI 1999 Advanced DATA Step Topics Neil H. Howard source 10
SUGI 1999 FUZZY MERGES: Examples and Techniques Malachy J. Foley source 10
SESUG 1998 MATCH-MERGING: 27 Plus Traps and How to Avoid Them Malachy J. Foley 10
SUGI 1998 MATCH-MERGIN G : 20 Some T raps and How to Avoid Them Malachy J. Foley source 21
SCSUG 1997 SAS-a-Sketch: Using SAS Annotate Facility for Creating Custom Graphs Patrick M. McGown 6
SUGI 1997 Reading and Writing Character Data Craig Dickstein,
Marge Scerbo		 source 8
SESUG 1996 A SAS Programmer's View of the SAS Supervisor H. Ian Whitlock 11
NESUG 1996 Reading and Writing Character Data Craig Dickstein,
Marge Scerbo		 8
SEUGI 1996 A few quick tips concerning base SAS software John R. Whittington source 4
SUGI 1996 Data Summary: Beyond the Basics Susan J. Slaughter,
Lora D. Delwiche		 source 7
SUGI 1996 Reading and Writing Character Data Craig Dickstein,
Marge Scerbo		 source 8
NESUG 1994 Avoiding, Accepting and Taking Advantage of Missing Data Warren Repole Jr. 10
SUGI 1994 Avoiding, Accepting and Taking Advantage of Missing Data Warren Repole Jr. source 9
SESUG 1993 How to "RETAIN" Your Sanity: Some Annotated Examples Ronald P. Cody,
Ray Pass		 6
NESUG 1992 How to "RETAIN" Your Sanity: Some Annotated Examples Ronald P. Cody,
Ray Pass		 8
NESUG 1991 Fuzzy Merges (How to Make MERGE Really Work) Jack N. Shoemaker 6
SUGI 1991 ERROR: What to Look for When Debugging SAS Programs Brit Minor source 6
SUGI 1991 Report Writing Using DATA Step Programming in Base SAS Software David A. Larson,
Charles R. Wartenberg Jr.		 source 3
SUGI 1982 Improving the Data Management Expertise of Experienced SAS Users Joshua Sharlin source 6

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