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562 papers and 7 presentations; 418 titles.

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Conference × Year × Title × Authors Extras Pages
WUSS 2026 Automating SDTM Subject Visits (SV) Derivation A Configuration-Driven, Meta-Programming Approach in SAS [presentation] Huiqing Chen source 15
WUSS 2026 SAS Essentials II: Introduction to DATA Step Programming [presentation] Susan J. Slaughter source 40
PharmaSUG 2026 DOSEON: Fuzzy Matching DOSE Date Intervals ON Analysis Dates Across SAS (PROC SQL, SAS Macro, DATA Step, and PROC FCMP) Inka Leprince,
Troy Martin Hughes		 source 39
PharmaSUG 2026 SAS Performance Tuning Techniques (From Slow to Scalable) Kirk Paul Lafler source 18
PharmaSUG 2026 SAS Programming techniques for efficiency and code optimization Jayanth Iyengar source 27
PHUSE US 2026 Fuzzy Matching DOSE Date Intervals ON Analysis Dates Across SAS (DATA Step, PROC SQL, SAS Macro, and PROC FCMP) Inka Leprince,
Troy Martin Hughes		 source
presentation source		 32
WUSS 2025 SAS Essentials II: Introduction to DATA Step Programming [presentation] Susan J. Slaughter source 40
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
PharmaSUG 2025 SET Statement Considered Harmful Bartosz Jabłoński source 21
PharmaSUG 2025 Slamming Datasets Together, Without Hurt, Using SAS, R and Excel David W. Franklin source 6
MWSUG 2024 Best Practices for Efficiency and Code Optimization in SAS programming Jayanth Iyengar source 20
MWSUG 2024 Stacking Up: Horizontal or Vertical with PROC SQL or DATA Step [presentation] Charu Shankar source 59
SESUG 2024 A Brief Introduction to DS2 Mark L. Jordan source 10
SESUG 2024 Advanced DATA Step Look-Back and Look-Ahead Techniques Joshua M. Horstman source 5
SESUG 2024 Look Up Not Down: Advanced Table Lookups in Base SAS Jayanth Iyengar source 20
WUSS 2024 Advanced DATA Step Look-Back and Look-Ahead Techniques Joshua M. Horstman source 5
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 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
SESUG 2023 Best Practices for Efficiency and Code Optimization in SAS programming Jayanth Iyengar source 20
SESUG 2023 SAS Program Efficiency for Beginners Bruce F. Gilsen source 15
PharmaSUG 2023 Best Practices for Efficiency and Code Optimization in SAS programming Jayanth Iyengar source 20
SESUG 2022 Functions (and More!) on CALL! Richann J. Watson,
Louise S. Hadden		 source 33
SESUG 2022 Getting Started with DATA Step Hash Objects Joshua M. Horstman source 8
WUSS 2022 Best Practices for Efficiency and Code Optimization in SAS programming Jayanth Iyengar source 21
WUSS 2022 Functions (and More!) on CALL! Richann J. Watson,
Louise S. Hadden		 source 33
WUSS 2022 Getting Started with DATA Step Hash Objects Joshua M. Horstman source 8
PharmaSUG 2022 Functions (and More!) on CALL! Richann J. Watson,
Louise S. Hadden		 source 33
PharmaSUG 2022 Look Up Not Down: Advanced Table Lookups in Base SAS Jayanth Iyengar,
Joshua M. Horstman		 source 28
PHUSE EU 2021 Differences in Performance Between the Options KEEP and WHERE as Compared to the Statements KEEP and IF in SAS Data Steps Ruurd Bennink source
video
presentation source		 8
SESUG 2021 Getting Started with DATA Step Hash Objects Joshua M. Horstman source 8
SESUG 2021 Getting Started with DATA Step Hash Objects Joshua M. Horstman source 8
SESUG 2021 NOBS for Noobs David B. Horvath source 4
PHUSE US 2021 R Shiny Application for the PHUSE Open Data Repository [presentation] Hanming Tu source
video		 15
PharmaSUG 2021 Mashing Two Datasets Together David W. Franklin source 5
PharmaSUG 2021 NOBS for Noobs David B. Horvath source 4
SGF 2021 If You Need These OBS and These VARS, Then Drop IF and Keep WHERE Jayanth Iyengar source 9
SESUG 2020 Efficiently Apply a Change File to a Large File via DATA Step MODIFY and _IORC_ Thomas E. Billings source 7
SESUG 2020 Look Up Not Down: Advanced Table Lookups in Base SAS Jayanth Iyengar,
Joshua M. Horstman		 source 28
SGF 2020 Accelerate DATA Step BY-Group Processing in SAS Viya Jason Secosky,
David Bultman		 source 14
SGF 2020 Best Practices in SAS Programming to Support Ever-Increasing Data Loads. John Schmitz source 15
SGF 2020 History Carried Forward, Future Carried Back: Mixing Time Series of Differing Frequencies Mark Keintz source 14
SGF 2020 Tips, Traps, and Techniques in BASE SAS for vertically combining SAS data sets Jayanth Iyengar source 18
SESUG 2019 NOBS for Noobs David B. Horvath source 4
SESUG 2019 SAS PROC IMPORT Troubleshooting Guide Imelda C. Go,
Wendi L. Wright		 source 12
MWSUG 2019 10 Cool Things You Can Do in a DATA STEP Stephanie R. Thompson 6
MWSUG 2019 Look Up Not Down: Advanced Table Lookups in Base SAS Jayanth Iyengar,
Joshua M. Horstman		 24
WUSS 2019 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman source 16
PharmaSUG 2019 History Carried Forward, Future Carried Back: Mixing Time Series of Differing Frequencies Mark Keintz source 11
PharmaSUG 2019 Python-izing the SAS Programmer Mike Molter source 19
SGF 2019 FETCH()ing Use Cases for the Data Access Functions Chad Mukherjee source 11
SGF 2019 HASH Beyond Lookups - Take Another Look Elizabeth Axelrod source 13
SGF 2019 Tips, Traps, and Techniques in BASE SAS for vertically combining SAS data sets Jayanth Iyengar source 18
SCSUG 2018 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman source 16
PHUSE EU 2018 Time Management: Programming Techniques to Positively Impact Runtimes Ian Sanderson source
presentation source		 9
MWSUG 2018 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman 16
MWSUG 2018 Tips, Traps, and Techniques in BASE SAS for vertically combining SAS data sets Jayanth Iyengar 18
WUSS 2018 Introduction to DATA Step Programming: SAS Basics II [presentation] Susan J. Slaughter source 40
WUSS 2018 Parallel Processing with Base SAS Jim Barbour source 17
PharmaSUG 2018 Beyond MERGE for Combining Datasets David W. Franklin source 4
PharmaSUG 2018 Discover the Deeper DATA Step Timothy J. Harrington source 14
PharmaSUG 2018 Exploring techniques of using multiple SET statements in a DATA step Yizhong Huang source 10
PharmaSUG 2018 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman source 16
PharmaSUG 2018 SAS Macros of Performing Look-Ahead and Look-Back Reads Yanhong Liu source 10
SGF 2018 If You Need These OBS and These VARS, Then Drop IF and Keep WHERE Jayanth Iyengar source 9
SGF 2018 Just Enough SAS Cloud Analytic Services: CAS Actions for SAS Visual Analytics Report Developers Michael Drutar source 14
SGF 2018 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman source 16
SGF 2018 Using Arrays to Quickly Perform Fuzzy Merge Look-ups: Case Studies in Efficiency Arthur L. Carpenter source 14
SESUG 2017 Hello World! Getting Started with the SAS DS2 Language Patricia S. Aanderud,
Jonathan Boase		 source 7
SESUG 2017 Leads and Lags: Static and Dynamic Queues in the SAS DATA STEP, 2nd ed. Mark Keintz source 15
PHUSE EU 2017 Check Your Code! Control Your Data! Kristina Zweier source
presentation source		 16
PHUSE EU 2017 Completing the Data Set Jigsaw: Hints and Tips for Assembling Data Sets Together Cerys Rand source
presentation source		 9
MWSUG 2017 Tackling Unique Problems by Using TWO SET Statements in ONE DATA Step Ben Cochran 9
MWSUG 2017 The Building Blocks of SAS Datasets - S-M-U (Set, Merge, and Update) Andrew T. Kuligowski 13
WUSS 2017 Effectively Utilizing Loops and Arrays in the DATA Step Arthur X. Li source 17
WUSS 2017 Introduction to DATA Step Programming: SAS Basics II Susan J. Slaughter 39
PharmaSUG 2017 Controlled Terminology Without Excel Mike Molter source 15
PharmaSUG 2017 Expansion of Opportunities in Programming: DS2 Features and Examples of Usage Object Oriented Programming in SAS Serhii Voievutkyi source 11
PharmaSUG 2017 Power of Interleaving and RETAIN Combination in Data Manipulation Zongming Pan source 10
SGF 2017 Going Green With Your SAS Applications Michael A. Raithel source 17
SGF 2017 Haven't I Seen You Before? An Application of DATA Step Hash for Efficient Complex Event Associations John Schmitz source
zip		 6
SGF 2017 Know Your Tools Before You Use Justin Jia source 16
SGF 2017 Leads and Lags: Static and Dynamic Queues in the SAS DATA STEP, 2nd ed. Mark Keintz source 15
SGF 2017 PROC DS2: What's in It for You? Viraj R Kumbhakarna source 11
SGF 2017 So You Think You Can Combine Data Sets? Christopher J. Bost source 23
SGF 2017 Yet Another Lookup Method: Updatable Indexed Data Sets Jack Hamilton source 15
SESUG 2016 If You Need These OBS and These VARS, Then Drop IF and Keep WHERE Jayanth Iyengar source 9
SESUG 2016 Leads and Lags: Static and Dynamic Queues in the SAS DATA STEP Mark Keintz source 15
PHUSE EU 2016 CompareDirectory - Macro Bits and Pieces in Action Lawrence Heaton-Wright source
presentation source		 7
PHUSE EU 2016 Top 10 Uses of Macro %VARLIST - In Proc SQL, Data Step and Elsewhere Jean-Michel Bodart source
presentation source		 12
MWSUG 2016 A Failure To EXIST: Why Testing for Data Set Existence with the EXIST Function Alone Is Inadequate for Serious Software Development in Asynchronous, Multiuser, and Parallel Processing Environments Troy Martin Hughes 8
MWSUG 2016 Implementing a Medicaid Claims Processing System using SAS software A Novel Implementation of BASE SAS Using Limited Resources in an Effective Manner Stephen C. DeVoyd 21
MWSUG 2016 Leads and Lags: Static and Dynamic Queues in the SAS DATA STEP Mark Keintz 15
WUSS 2016 PROC DS2: What's in It for You? Viraj R Kumbhakarna source 11
PharmaSUG 2016 SAS Techniques for Managing Large Datasets Rucha Landge source 7
SGF 2016 An Insider's Guide to SAS/ACCESS Interface to Impala Jeffrey Bailey source 19
SGF 2016 Exploring SAS Embedded Process Technologies on Hadoop David Ghazaleh source 17
SGF 2016 Have it Your Way: Creating Reports with the DATA Step Report Writing Interface Peter J. Lund source 27
SGF 2016 High-Performance Data Access with FedSQL and DS2 Shaun Kaufmann source 13
SGF 2016 Leads and Lags: Static and Dynamic Queues in the SAS DATA STEP Mark Keintz source 15
SGF 2016 Omitting Records with Invalid Default Values Lily Yu source
zip		 6
SGF 2016 Running Text Analytics Models in Hadoop David Bultman,
Adam Pilz		 source
zip		 13
SGF 2016 Shuffle Up and Deal! Sampling without Replacement Using SAS Daniel R. Bretheim source
presentation		 9
SGF 2016 Tips and Techniques for User-Defined Packages in SAS DS2 Chris Brooks source 20
MWSUG 2015 Table Lookup Techniques: From the Basics to the Innovative Arthur L. Carpenter 11
PHUSE EU 2015 WPP, Worst Programming Practice - Real-life Pittfalls in Everyday Clinical Programming: Why and How Hannes Engberg Raeder,
Rowland Hale		 source
presentation source		 14
SESUG 2015 How to DoW Paul M. Dorfman source 12
SESUG 2015 Tales from the Help Desk 6: Solutions to Common SAS Tasks Bruce F. Gilsen source 11
SESUG 2015 The Mystery of Automatic Retain in a SAS Data Step Huei-Ling Chen source 8
WUSS 2015 A Brief Introduction to Some Object-Oriented Programming (OOP) Concepts for SAS Programmers Andra Northup source 19
WUSS 2015 DATA Step Merging Techniques: From Basic to Innovative Arthur L. Carpenter source 12
WUSS 2015 Leads and Lags: Static and Dynamic Queues in the SAS DATA STEP Mark Keintz source 15
WUSS 2015 S-M-U (Set, Merge, and Update) Revisited Andrew T. Kuligowski source 13
WUSS 2015 The Data Set statement: What are my options? Mark Kirkham source 5
WUSS 2015 Using Arrays to Quickly Perform Fuzzy Merge Look-ups: Case Studies in Efficiency Arthur L. Carpenter source 14
PharmaSUG CN 2015 Effectively Utilizing Loops and Arrays in the DATA Step Arthur X. Li 17
PharmaSUG 2015 DATA Step Merging Techniques: From Basic to Innovative Arthur L. Carpenter source 12
PharmaSUG 2015 Inside the DATA Step: Pearls of Wisdom for the Novice SAS Programmer Joshua M. Horstman,
Britney D. Gilbert		 source 11
PharmaSUG 2015 PROC TRANSPOSE For Fun And Profit John J. Cohen source 18
PharmaSUG 2015 Using Arrays to Quickly Perform Fuzzy Merge Look-ups: Case Studies in Efficiency Arthur L. Carpenter source 14
SGF 2015 A Practical Guide to SAS Extended Attributes Chris Brooks source 9
SGF 2015 Inside the DATA Step: Pearls of Wisdom for the Novice SAS Programmer Joshua M. Horstman,
Britney D. Gilbert		 source 11
SGF 2015 Introduction to SAS Hash Objects Christopher W. Schacherer source 26
SGF 2015 Leads and Lags: Static and Dynamic Queues in the SAS DATA STEP Mark Keintz source
zip		 14
SGF 2015 S-M-U (Set, Merge, and Update) Revisited Andrew T. Kuligowski source 13
SGF 2015 SAS and Hadoop. 4th Annual State of the Union [presentation] Paul Kent source 70
SGF 2015 Table Lookup Techniques: From the Basics to the Innovative Arthur L. Carpenter source 11
SESUG 2014 PROC TRANSPOSE For Fun And Profit John J. Cohen source 18
SESUG 2014 The DoW-Loop Paul M. Dorfman,
Lessia S. Shajenko		 source 12
SESUG 2014 The Nuances of Combining Hospital Data Jontae Sanders,
Charlotte Baker,
C. Perry Brown		 source 5
SESUG 2014 The Power of PROC APPEND Ted Logothetti source 7
PHUSE EU 2014 Call Execute: Let Your Program Run Your Macro Artur Usov source
presentation source		 9
MWSUG 2014 DATA Step Merging Techniques: From Basic to Innovative Arthur L. Carpenter 11
MWSUG 2014 DS2: The New and Improved DATA Step in SAS Rajesh Lal 11
MWSUG 2014 Ignorance is Not Bliss: Pearls of Wisdom for the Novice SAS Programmer Joshua M. Horstman,
Britney D. Gilbert		 9
MWSUG 2014 Introduction to SAS Hash Objects Christopher W. Schacherer 26
MWSUG 2014 PROC SQL for DATA Step Die-Hards Christianna S. Williams 22
MWSUG 2014 Using Arrays to Quickly Perform Fuzzy Merge Look-ups: Case Studies in Efficiency Arthur L. Carpenter 14
WUSS 2014 LEADS AND LAGS: HANDLING QUEUES IN THE SAS DATA STEP Mark Keintz source 12
WUSS 2014 Table Lookup Techniques: From the Basics to the Innovative Arthur L. Carpenter source 11
PharmaSUG 2014 Indexing: A powerful technique for improving efficiency Arun Raj Vidhyadharan,
Sunil Mohan Jairath		 source 9
PharmaSUG 2014 Table Lookup Techniques: From the Basics to the Innovative Arthur L. Carpenter source 11
PharmaSUG 2014 Understanding and Applying the Logic of the DOW-Loop Arthur X. Li source 12
SGF 2014 DATA Step Merging Techniques: From Basic to Innovative Arthur L. Carpenter source 10
SGF 2014 Effectively Utilizing Loops and Arrays in the DATA Step Arthur X. Li source 17
SGF 2014 Have it Your Way: Creating Reports with the DATA Step Report Writing Interface Peter J. Lund source 27
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 "How Do I...?" There Is More Than One Way To Solve That Problem; Why Continuing To Learn Is So Important Arthur L. Carpenter source 20
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
SCSUG 2013 Introduction to SAS Hash Objects Christopher W. Schacherer source 26
SESUG 2013 Coding For the Long Haul With Managed Metadata and Process Parameters Mike Molter source 20
SESUG 2013 HOW to DOW Paul M. Dorfman source 12
SESUG 2013 PEEKing at Roadway Segments Carol A. Martell source 12
MWSUG 2013 "How Do I...?" There Is More Than One Way To Solve That Problem; Why Continuing To Learn Is So Important Arthur L. Carpenter 20
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
MWSUG 2013 The Secret Life of DATA STEP Swati Agarwal 10
NESUG 2013 I Can SQL Clearly Now, the Data's Fine... Brian Taaffe 16
NESUG 2013 Leads and Lags in SAS Mark Keintz 11
NESUG 2013 PROC TRANSPOSE For Fun And Profit John J. Cohen 18
PharmaSUG 2013 "How Do I...?" There Is More Than One Way To Solve That Problem; Why Continuing To Learn Is So Important Arthur L. Carpenter source 20
PharmaSUG 2013 Coding For the Long Haul With Managed Metadata and Process Parameters Mike Molter source 20
PharmaSUG 2013 Doing the hashwork: Using the DATA step hash object to perform common clinical programming chores Miles Dunn source 9
PharmaSUG 2013 Effectively Utilizing Loops and Arrays in the DATA Step Arthur X. Li source 17
PharmaSUG 2013 SQL, HASH Tables, FORMAT and KEY= - More Than One Way to Merge Two Datasets David W. Franklin source 5
SGF 2013 "How Do I...?" There Is More Than One Way To Solve That Problem; Why Continuing To Learn Is So Important Arthur L. Carpenter source 19
SGF 2013 30 in 20 Things You May Not Know about SAS Tim Berryhill source 8
SGF 2013 Developer Reveals: Extended Data Set Attributes Diane Olson source 9
SGF 2013 Have it Your Way: Creating Reports with the DATA Step Report Writing Interface Peter J. Lund source 27
NESUG 2012 Combining Continuous Events and Calculating Duration in Kaplan-Meier Analysis Using a Single DATA Step Hui Song,
George Laskaris		 8
NESUG 2012 Condensed and Sparse Indexes for Sorted SAS Datasets Mark Keintz 16
NESUG 2012 Interesting Technical Mini-Bytes of Base SAS - From DATA Step to Macros Airaha Chelvakkanthan Manickam 13
NESUG 2012 PROC SQL for DATA Step Die-Hards Christianna S. Williams 20
PHUSE EU 2012 Reprogramming a Many-to-Many Merge with Hash Objects David J. Garbutt source
presentation source		 24
SESUG 2012 Fatal Witlessness: Appending Datasets! WARNING! This may cause truncation of data! Arunim Gupta source 7
SESUG 2012 Learning PROC SQL the DATA Step Way Meghal Parikh source 8
SESUG 2012 Mastering the Basics: Preventing Problems by Understanding How SAS Works Imelda C. Go source 14
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
MWSUG 2012 Innovative Techniques: Doing More with Loops and Arrays Arthur L. Carpenter 14
WUSS 2012 Countdown of the Top 10 Ways to Merge Data David W. Franklin source 6
WUSS 2012 Innovative Techniques: Doing More with Loops and Arrays Arthur L. Carpenter source 14
PharmaSUG 2012 Innovative Techniques: Doing More with Loops and Arrays Arthur L. Carpenter source 13
PharmaSUG 2012 Interesting Technical Mini-Bytes of Base SAS - From DATA Step to Macros Airaha Chelvakkanthan Manickam source 13
PharmaSUG 2012 The Use and Abuse of the Program Data Vector James R. Johnson source 23
SGF 2012 HOW to DOW Paul M. Dorfman,
Lessia S. Shajenko		 source 12
SGF 2012 Implementing Control Selection Using Hash Tables: A Case Study Craig Kasper source 10
SGF 2012 Interesting Technical Mini-Bytes of Base SASFrom DATA Steps to Macros Airaha Chelvakkanthan Manickam source 13
SGF 2012 Selecting Unrestricted and Simple Random With Replacement Samples Using Base SAS and PROC SURVEYSELECT David D. Chapman source 14
SGF 2012 The DOW Loop: A Smarter Approach to Your Existing Code Fuad J. Foty source 12
SGF 2012 The Use and Abuse of the Program Data Vector James R. Johnson source 23
SESUG 2011 Condensed and Sparse Indexes for Sorted SAS Datasets Mark Keintz source 16
SESUG 2011 ExcelXP on Steroids: Adding Custom Options To The ExcelXP Tagset Mike Molter source 14
SESUG 2011 In Lockstep with the DoW-Loop Paul M. Dorfman,
Lessia S. Shajenko		 source 18
WUSS 2011 Output SAS DATA Step Views: an Experimental Feature Thomas E. Billings source 9
MWSUG 2011 Using a Double DOW Loop to Compute Progression Free Survival Matthew Nizol 9
NESUG 2011 Hash + Point = Key Paul M. Dorfman,
Lessia S. Shajenko		 13
NESUG 2011 PROC SQL for DATA Step Die-Hards Christianna S. Williams 22
PharmaSUG 2011 ExcelXP on Steroids: Adding Custom Options To The ExcelXP Tagset Mike Molter source 14
PharmaSUG 2011 Processing the RefSeq and CCDS Annotation Datasets Using the SAS System: Creation of Gene Reference Kevin R. Viel,
Shannon Grabich		 source 9
PharmaSUG 2011 The Many Ways to Effectively Utilize Array Processing Arthur X. Li source 14
PharmaSUG 2011 Using Two SET Statements in One DATA Step Ben Cochran source 5
SGF 2011 ExcelXP on Steroids: Adding Custom Options To The ExcelXP Tagset Michael J. Molter source 14
SGF 2011 Longitudinal Data Techniques: Looking Across Observations Ronald P. Cody source 7
SGF 2011 The Essence of DATA Step Programming Arthur X. Li source 19
SGF 2011 The Many Ways to Effectively Utilize Array Processing Arthur X. Li source 14
NESUG 2010 Automatically Converting Character Variables That Store Numbers to Numeric Variables Christopher J. Bost 13
NESUG 2010 Condensed and Sparse Indexes for Sorted SAS Datasets Mark Keintz 16
NESUG 2010 Find() the power of Hash - How, Why and When to use the SAS Hash Object John Blackwell 5
NESUG 2010 HOW to DOW Paul M. Dorfman 18
NESUG 2010 How to Think Through the SAS DATA Step H. Ian Whitlock 17
NESUG 2010 Table Lookup in SAS Weili Yang,
Fang K. Chen,
Liping Zhang,
Wenyu Hu		 7
SCSUG 2010 Beyond the Simple Merge in SAS Vanessa Cox source 6
SCSUG 2010 Take Control: Understanding and Controlling Your Do-Loops Sarah Woodruff,
Toby Dunn		 source 21
WUSS 2010 A SAS Output Delivery System Menu for All Appetites and Applications Chevell T. Parker source 25
WUSS 2010 Get a Grip on Arrays in Just 50 Minutes! Arthur X. Li source 14
WUSS 2010 Longitudinal Data Techniques: Looking Across Observations Ronald P. Cody source 7
WUSS 2010 The Building Blocks of SAS Datasets - S-M-U (Set, Merge, and Update) Andrew T. Kuligowski source 13
WUSS 2010 Transitive Record Linkage in SAS using SET / KEY= and MODIFY / POINT= Denis Hulett source 8
PHUSE EU 2010 APPEND, EXECUTE and MACRO Jim Groeneveld source
presentation source		 7
MWSUG 2010 Set, Match, Merge ... Don't You Love SAS Peter W. Eberhardt,
Ying Liu		 19
MWSUG 2010 Using a Few Key Elements of SAS DATA Step Code and a Couple of Procedures to Optimize the Observation Length of a Data Set Philip A. Wright 9
SESUG 2010 IF and %IF You Don't Understand H. Ian Whitlock source 6
SESUG 2010 Set, Match, Merge ... Don't You Love SAS Peter W. Eberhardt,
Ying Liu		 source 19
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
PharmaSUG 2010 Countdown of the Top 10 Ways to Merge Data David W. Franklin 6
SGF 2010 Complex Data Combinations on Large Volumes: How to Get the Best Performance Henri Theuwissen source 22
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 Look Before You Leap A Technique to Simulate a Look-Ahead Function Leonard E. Landry source 5
SGF 2010 Using a Few Key Elements of SAS DATA Step Code and a Couple of Procedures to Optimize the Observation Length of a Data Set Philip A. Wright source 9
SGF 2010 Using the Descriptor Portion of a SAS Data File Dragos D. Capan source 6
SCSUG 2009 Working with Longitudinal Data Ronald P. Cody 4
SESUG 2009 Don't Be a SAS Dinosaur: Modernizing Programs with Base SAS 9.2 Enhancements Warren Repole Jr. source 11
PHUSE EU 2009 Practical Uses of the DOW Logo in Pharmaceutical Programming Richard R. Allen source 10
PHUSE EU 2009 Works as Designed (?) Heinrich von Lips source 7
MWSUG 2009 Dietary Glycemic Load and Risk of Colon Cancer: A Guide to Data Management Svetlana Zelenskiy,
Lauren Byrne,
Cheryl L. Thompson,
Thomas C. Tucker,
David Bruckman,
Li Li		 16
MWSUG 2009 Table Lookups: From IF-THEN to Key-Indexing Arthur L. Carpenter 10
MWSUG 2009 Using the Data Step's ATTRIB Statement to both Manage and Document Variables in a SAS Dataset (lightly) Philip A. Wright 8
PNWSUG 2009 Multiple Set Statements in a Data Step: A Powerful Technique for Combining and Aggregating Complex Data Renu Gehring 11
NESUG 2009 PROC SQL for DATA Step Die-Hards Christianna S. Williams 19
NESUG 2009 The Building Blocks of SAS Datasets - S-M-U (Set, Merge, and Update) Andrew T. Kuligowski 13
NESUG 2009 The DOW-Loop Unrolled Paul M. Dorfman,
Marina Fridman		 18
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
WUSS 2009 The Fundamentals of DATA Step Programming II: Looping Arthur X. Li source 13
PharmaSUG 2009 A SAS Output Delivery System Menu for All Appetites and Applications Chevell T. Parker 25
PharmaSUG 2009 One-Step Change from Baseline Calculations Nancy Brucken 5
PharmaSUG 2009 Sweet Smell of SucSAS - When Your DATA Step Does What is Intended!! Arthur X. Li 19
SGF 2009 A Faster Index for Sorted SAS Datasets Mark Keintz source 9
SGF 2009 A SAS Output Delivery System Menu for All Appetites and Applications Chevell T. Parker source 25
SGF 2009 Don't Be a SAS Dinosaur: Modernizing Programs with Base SAS 9.2 Enhancements Warren Repole Jr. source 11
SGF 2009 E-Mail z/OS CICS Exception Reports in Plain Text Format Using DATA _NULL_ and MXG Software Neal Musitano Jr. source 8
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 One-Step Change from Baseline Calculations Nancy Brucken source 4
SGF 2009 The DOW-Loop Unrolled Paul M. Dorfman,
Koen Vyverman		 source 18
SGF 2009 The Perils of End-of-File Processing When Subsetting Data Leonard E. Landry source 7
WUSS 2008 A Sampler of What's New in Base SAS 9.2 Jason Secosky source 15
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
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
SESUG 2008 Using Lookup Tables to Match Data Wenyu Hu,
Fang K. Chen,
Liping Zhang		 source 7
MWSUG 2008 A Sampler of What's New in Base SAS 9.2 Jason Secosky 15
MWSUG 2008 One-Step Change from Baseline Calculations, and Other DOW-Loop Tricks Nancy Brucken 8
PNWSUG 2008 A Sampler of What's New in Base SAS 9.2 Jason Secosky 15
PNWSUG 2008 MODIFY The Most Under-Appreciated of the Data Step File Handling Statements Curtis E. Mack 12
PNWSUG 2008 New in SAS 9.2: It's the Little Things that Count Diane Olson 7
NESUG 2008 A Faster Index for Sorted SAS Datasets Mark Keintz 11
NESUG 2008 A Sampler of What's New in Base SAS 9.2 Jason Secosky 15
NESUG 2008 The DOW-Loop Unrolled Paul M. Dorfman 18
PharmaSUG 2008 An Animated Guide: Speed Merges with Key Merging and the _IORC_ Variable Russell M. Lavery 9
PharmaSUG 2008 Join, Merge or Lookup? Expanding your toolkit Judy Loren,
Sandeep Gaudana		 16
PharmaSUG 2008 One-Step Change from Baseline Calculations Nancy Brucken 5
PharmaSUG 2008 The DOW-Loop Unrolled Paul M. Dorfman,
Lessia S. Shajenko		 18
PharmaSUG 2008 When PROC APPEND May Make More Sense Than the DATA Step David W. Carr 6
SGF 2008 Many-to-Many Merges in the DATA Step Edward Heaton source 9
SGF 2008 New in SAS 9.2: It's the Little Things that Count Diane Olson source 7
SGF 2008 SET, MERGE and beyond. Erik W. Tilanus source 15
SGF 2008 Using a SAS Table to Drive Any Macro Michael D. Whitaker source 12
SGF 2008 Using the SAS DATA Step and PROC SQL to Create Macro Arrays Stuart D. Long,
Edward Heaton		 source 11
SGF 2008 When PROC APPEND May Make More Sense Than the DATA Step David W. Carr source 6
NESUG 2007 Comparing Values Across Observations: Be Careful Prafulla Girase 4
NESUG 2007 Data Without (Step) Boundaries Felix Galbis-Reig 7
NESUG 2007 Outperforming SAS Indices for Sorted Datasets Mark Keintz,
Shuguang Zhang		 8
NESUG 2007 The Power and the Trap of Automatic Retain Yunchao (Susan) Tian 6
NESUG 2007 The Program Data Vector As an Aid to DATA step Reasoning Marianne L. Whitlock 13
NESUG 2007 Using the SAS DATA Step and PROC SQL to Create Macro Arrays Stuart D. Long,
Edward Heaton		 11
SESUG 2007 Set, Match, Merge ... Don't You Love SAS Peter W. Eberhardt,
Ying Liu		 source 19
SESUG 2007 The DOW-Loop Unrolled Paul M. Dorfman,
Lessia S. Shajenko		 source 18
MWSUG 2007 Getting Started with the DATA Step Hash Object Jason Secosky,
Janice Bloom		 9
WUSS 2007 Hurry!!!, Hurry!!! Step Right UP. Use The "Magical Compound Where Clause" to Eliminate Data Steps, Reduce Processing Steps, Speed Job Turnaround, and Mystify Your Friends William E. Benjamin Jr. source 6
WUSS 2007 The Power of the BY Statement Toby Dunn,
Paul A. Choate		 source 16
PHUSE EU 2007 Comparison of different ways using table lookups on huge tables Ralf Minkenberg source 6
SCSUG 2007 Explaining Unexpected Log Messages and Output Results from DATA Step Code Debbie Buck,
Larry Stewart		 13
SCSUG 2007 How to Incorporate Old SAS Data into a New DATA Step, or "What is S-M-U?" Andrew T. Kuligowski 9
SCSUG 2007 The Power of the BY Statement Toby Dunn,
Paul A. Choate		 11
PNWSUG 2007 How to Incorporate Old SAS Data into a New DATA Step, or "What is S-M-U?" Andrew T. Kuligowski 9
PharmaSUG 2007 Getting Started with the DATA Step Hash Object Jason Secosky,
Janice Bloom		 9
SGF 2007 Data Matching David H. Dickinson,
Wendy B. Johnson		 source 18
SGF 2007 DATA Step vs. PROC SQL: What's a Neophyte to Do? Ray Davis,
Michael L. Dickstein,
Craig Pass		 source 12
SGF 2007 Getting Started with the DATA Step Hash Object Jason Bloom,
Janice Secosky		 source 9
SGF 2007 How to Think Through the SAS DATA Step H. Ian Whitlock source 19
SGF 2007 Hurry!!!, Hurry!!! Step Right UP. Use The "Magical Compound Where Clause" to Eliminate Data Steps, Reduce Processing Steps, Speed Job Turnaround, and Mystify Your Friends William E. Benjamin Jr. source 6
SGF 2007 The Power of the BY Statement Paul A. Dunn,
Toby Choate		 source 16
PNWSUG 2006 Getting Started with the DATA Step Hash Object Jason Secosky,
Janice Bloom		 10
PNWSUG 2006 MODIFY The Most Under-Appreciated of the Data Step File Handling Statements Curtis E. Mack 12
MWSUG 2006 Accuracy or Efficiency in Merging Cindy Liu 6
MWSUG 2006 How to Incorporate Old SAS Data into a New DATA Step, or "What is S-M-U?" Andrew T. Kuligowski 9
SCSUG 2006 Getting Started with the DATA Step Hash Object Jason Secosky,
Janice Bloom		 10
PHUSE EU 2006 An Introduction to PROC SQL Anthony Cooper source 20
SESUG 2006 How to Think Through the SAS DATA Step H. Ian Whitlock source 20
NESUG 2006 An Introduction to Reshaping (TRANSPOSE) and Combining (MATCH-MERGE) SAS Data Sets Michael S. Zdeb 15
NESUG 2006 By's Notsorted Option Karuna Samudral,
Gregory Giddings		 11
NESUG 2006 Exporting & Importing Datasets & Catalogs: Utility Macros Adel Fahmy 12
NESUG 2006 Matching with Propensity Scores to Reduce Bias in Observational Studies Marcelo Coca-Perraillon,
Nan Liu		 10
NESUG 2006 Subsetting Observations from Large SAS Data Sets Christopher J. Bost 6
PharmaSUG 2006 The Skinny on Processing Very Large Health Claims Data Sets Gopal Rajagopal,
Blue Bell		 10
SUGI 2006 A Hands-On Introduction to SAS Basics and the SAS Display Manager Debbie Buck - SC source 12
SUGI 2006 A System of SAS Macros for Producing Statistical Reports Greg A. Grandits source 7
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 How to Think Through the SAS DATA Step H. Ian Whitlock source 20
SUGI 2006 Improve Database Transaction Processing Using MODIFY, the Most Under-Appreciated DATA Step File-Handling Statement Curtis E. Mack source 12
SUGI 2006 SQL Set Operators: So Handy Venn You Need Them Howard L. Schreier source 18
SUGI 2006 The SQL Procedure - A Primer for SAS Programmers Jimmy A. DeFoor source 17
PNWSUG 2005 MODIFY The Most Under-Appreciated of the Data Step File Handling Statements Curtis E. Mack 12
PNWSUG 2005 Table Lookups: From IF-THEN to Key-Indexing Arthur L. Carpenter 10
SESUG 2005 How SAS Thinks Neil H. Howard source 19
SESUG 2005 Laziness, Impatience, Hubris: Personality Traits of a Great Programmer John E. Bentley source 9
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
SCSUG 2005 Join, Merge or Lookup? Expanding your toolkit Judy Loren,
Sandeep Gaudana		 15
SCSUG 2005 Proc SQL - A Primer for SAS Programmers Jimmy A. DeFoor 17
WUSS 2005 Get It Together: Combining Data with SAS MERGE, UPDATE, and SET Mel Widawski source 12
WUSS 2005 SAS Essentials Neil H. Howard source 19
NESUG 2005 Database ACCESS Basics: SQL and Data Step Interface to Relational Databases Ashley Sanders 8
NESUG 2005 HOLY MACRO! An Intuitive Approach to Understanding the Macro Facility Michael J. Molter 20
NESUG 2005 How SAS Thinks Neil H. Howard 19
NESUG 2005 Join, Merge or Lookup? Expanding your toolkit Judy Loren,
Sandeep Gaudana		 15
PharmaSUG 2005 Advance Tips for Manipulating Data in commonly used SAS Procedures Raj Suligavi,
Jyotheeswar N Yellanki		 11
PharmaSUG 2005 How SAS Thinks Neil H. Howard 20
PharmaSUG 2005 Preventing Data Loss when Combining SAS Datasets John Cantrell 9
SUGI 2005 A Hands-On Introduction to SAS DATA Step Programming Debbie Buck - SC source 8
SUGI 2005 Explaining Unexpected Log Messages and Output Results from DATA Step Code Debbie Buck - SC,
Larry Stewart		 source 13
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 Slicing and Dicing the SAS Data Set William C. Murphy source 5
SUGI 2005 The Basics of Using SAS Indexes Michael A. Raithel source 9
NESUG 2004 An Animated Guide: An Animated Guide: Speed Merges with Key Merging and the _IORC_ Variable Russell M. Lavery 6
NESUG 2004 An Animated Guide: Speed Merges: Resource Use by Common Non-parallel Procedures Russell M. Lavery 8
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
SESUG 2004 Creating and Exploiting SAS Indexes Michael A. Raithel source 9
SESUG 2004 Here's the Data, Here's the Report I Want - How Do I Get There? Deborah B. Buck source 8
SESUG 2004 How to Incorporate Old SAS Data into a New DATA Step, or "What is S-M-U?" Andrew T. Kuligowski source 13
SESUG 2004 Taking it Home and Putting it into Practice Diane Cunningham source 8
SESUG 2004 Why the DATA Step Does What It Does Neil H. Howard source 19
WUSS 2004 How to Add to Existing Data or, Why Did You Do it That Way? Kathryn A. Valdes source 14
WUSS 2004 Table Lookups: From IF-THEN to Key-Indexing Arthur L. Carpenter source 10
MWSUG 2004 Don't Resort to Re-Sort Elizabeth Axelrod 3
PNWSUG 2004 How to Incorporate Old SAS Data into a New DATA Step, or "What is S-M-U?" Andrew T. Kuligowski 9
PNWSUG 2004 SAS Programming for Job Security: Tips and Techniques Revisited Arthur L. Carpenter 10
SUGI 2004 Creating and Exploiting SAS Indexes Michael A. Raithel source 10
SUGI 2004 DATA Step vs. PROC SQL: What's a Neophyte to Do? Craig Dickstein,
Ray Pass		 source 13
SUGI 2004 How to Incorporate Old SAS Data into a New DATA Step, or "What is S-M-U?" Andrew T. Kuligowski source 14
SUGI 2004 Quicker Than Merge? Kirby L. Cossey source 7
WUSS 2003 An Animated Guide: Speed Merges with Key Merging and the _IORC_ Variable Russell M. Lavery source 3
WUSS 2003 Table Lookups: From IF-THEN to Key-Indexing Arthur L. Carpenter source 7
SCSUG 2003 How to Incorporate Old SAS Data into a New DATA Step, or "What is S-M-U?" Andrew T. Kuligowski 10
SCSUG 2003 Quicker Than Merge? Kirby L. Cossey 5
NESUG 2003 Interleaving a Dataset with Itself: How and Why Howard L. Schreier 6
NESUG 2003 User Implementation and Revision of Business Rules Without Hard Coding: Macro-Generated SAS Code Michael Krumenaker,
Jit Bhattacharya		 11
VIEWS 2003 Which Merge? Steve Hanks presentation 3
PharmaSUG 2003 Application of Some Advanced PROC SQL Features in Clinical Trial Programming Changhong Shi 6
PharmaSUG 2003 Electronic Submission of SAS Data and Catalogs Simplified Adel Fahmy 6
PharmaSUG 2003 Selecting Balanced Cohorts for Comparison in Observational Research Craig Roberts 4
PharmaSUG 2003 The Use and Abuse of the Program Data Vector Jim Johnson 10
PharmaSUG 2003 Using Indexes to Perform Table Look-up Sandra Lynn Aker 4
SUGI 2003 Combining Summary Level Data with Individual Records Frank J. Ivis source 3
SUGI 2003 The DOW (Not that DOW!!!) and the LOCF in Clinical Trials Venky Chakravarthy source 4
SCSUG 2002 A FIRST . (but not LAST.) Word on the BY-group Processing Christine A. Smiley 9
NESUG 2002 An Animated Guide: Power Merging with Key/_IORC_ Merges Russell M. Lavery 5
NESUG 2002 How to Incorporate Old SAS Data into a New DATA Step, or "What is S-M-U?" Andrew T. Kuligowski 9
NESUG 2002 Longitudinal Data Techniques: Looking Across Observations Ronald P. Cody 6
NESUG 2002 Off and Running with Arrays in SAS Stephen Keelan 7
NESUG 2002 SAS Techniques for Incorporating Medical Code Updates into Longitudinal Health Care Data Perry Watts,
Alan C. Wilson		 10
PharmaSUG 2002 Efficient Interpolation Calculation Julia Z. Zhang 4
PharmaSUG 2002 Save Time Today Using SAS Views Robert S. Ray 4
SUGI 2002 Data Cleaning 101 Ronald P. Cody source 10
SUGI 2002 DATA Step vs. PROC SQL: What's a Neophyte to Do? Craig Dickstein,
Ray Pass		 source 9
SUGI 2002 How to Incorporate Old SAS Data into a New DATA Step, or "What is S-M-U?" Andrew T. Kuligowski source 9
SUGI 2002 Longitudinal Data Techniques: Looking Across Observations Ronald P. Cody source 4
SUGI 2002 Off and Running with Arrays in SAS Stephen A. Keelan source 7
SUGI 2002 SAS Accessing DB2 Data: a Performance Victory Away Henri Theuwissen,
Nancy Croonen		 source 9
SUGI 2002 Save Time Today Using SAS Views Robert S. Ray source 4
SUGI 2002 Table Look-up: Techniques Beyond the Obvious Henri Theuwissen,
Nancy Croonen		 source 9
MWSUG 2001 Confessions of a SAS System Electronic Mail Junkie Derek P. Morgan 4
MWSUG 2001 Table Lookups: From IF-THEN to Key-Indexing Arthur L. Carpenter 8
NESUG 2001 INTERPOLATION CALCULATION MADE EZ Julia Z. Zhang,
David C. Chen		 4
NESUG 2001 SAS Program Efficiency for Beginners Bruce F. Gilsen 10
NESUG 2001 Selecting Unrestricted and Simple Random With Replacement Samples Using Base SAS and PROC SURVEYSELECT David D. Chapman 9
WUSS 2001 Table Lookups: From IF-THEN to Key-Indexing Arthur L. Carpenter source 8
SESUG 2001 Manipulating Data: Elements of the DATA Step Language Paul M. Dorfman source 10
SESUG 2001 Point, Set, Match (Merge) - A Beginner's Lesson Jennifer Hoff Lindquist source 8
SESUG 2001 Using Functions and Arrays in the SAS System to Manage and Manipulate Data Ben Cochran source 6
SCSUG 2001 Manipulating Data: Elements of the DATA Step Language Paul M. Dorfman 10
SCSUG 2001 Passing Along SAS Data - SET, MERGE, and UPDATE Andrew T. Kuligowski 9
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 Data Cleaning 101 Ronald P. Cody source 10
SUGI 2001 DATA Step vs. PROC SQL: What's a Neophyte to Do? Craig Dickstein source 9
SCSUG 2000 Programming for Job Security Revisted: Even More Tips and Techniques to Maximize Your Indispensability Arthur L. Carpenter,
Tony Payne		 15
SESUG 2000 How to Incorporate Old SAS Data into a New DATA Step, or "What is S-M-U?" Andrew T. Kuligowski source 9
NESUG 2000 Longitudinal Data Techniques: Looking Across Observations Ronald P. Cody 6
NESUG 2000 Moving a Large SAS System Into an MVS Production Environment The Trials and Tribulations Bernard Gardocki,
Stephen J. Rhoades		 6
NESUG 2000 SAS Program Efficiency for Beginners Bruce F. Gilsen 10
WUSS 2000 How to Incorporate Old SAS Data into a New DATA Step, or "What is S-M-U?" Andrew T. Kuligowski source 7
WUSS 2000 Power Indexing: A Guide to Using Indexes Effectively in Nashville Releases Diane Olson source 5
MWSUG 2000 Power Indexing: A Guide to Using Indexes Effectively in Nashville Releases Diane Olson 5
MWSUG 2000 The SAS System Electronic Mail Interface: A Case Study Derek P. Morgan 3
SEUGI 2000 Moving to SAS Version 8 with Oracle Clare Somerville,
Colin J. Harris		 source 8
PharmaSUG 2000 GLOBAL INTEGRATED DATABASE (GIDB): Not Just a SET Statement Marla A. Childers 4
PharmaSUG 2000 How MERGE Really Works Bob Virgile 12
PharmaSUG 2000 POINT: A useful way to get around your data Greg Silva 4
PharmaSUG 2000 Subject Profiles: (Almost) as easy as 1, 2, 3 Greg Silva 4
SUGI 2000 How to Incorporate Old SAS Data into a New DATA Step, or "What is S-M-U?" Andrew T. Kuligowski source 7
SUGI 2000 Power Indexing: A Guide to Using Indexes Effectively in Nashville Releases Diane Olson source 5
SUGI 2000 The SAS System E-mail Interface: A Case Study Derek P. Morgan source 3
SCSUG 1999 Longitudinal Data Techniques Ronald P. Cody 6
NESUG 1999 Data Cleaning 101 Ronald P. Cody 10
NESUG 1999 How MERGE Really Works Bob Virgile 7
NESUG 1999 How Should I Combine My Data, Is The Question Stephen Thompson,
Asha Sharma		 6
NESUG 1999 Longitudinal Data Techniques: Looking Across Observations Ronald P. Cody 6
NESUG 1999 SAS Program Efficiency for Beginners Bruce F. Gilsen 10
NESUG 1999 The RETAIN Statement: One Window into the SAS Data Step Paul Gorrell 6
SEUGI 1999 ThinProway-A Java client to a SAS application - A successful story. Exactly what you need? Riccardo Proni source 9
SUGI 1999 Programming Idioms Using the SET Statement Jack E. Fuller source 6
SUGI 1999 SAS Program Efficiency for Beginners Bruce F. Gilsen source 9
SUGI 1999 The DATA Statement: Efficiency Techniques S. David Riba source 8
NESUG 1998 SAS Program Efficiency for Beginners Bruce F. Gilsen 10
SESUG 1998 DATA Step in Version 7: What's New? William F. Heffner 8
SESUG 1998 The Program Data Vector As an Aid to DATA step Reasoning Marianne L. Whitlock 10
SUGI 1998 DATA Step in Version 7: What's New? William F. Heffner source 8
SUGI 1998 Optimizing SAS Access to an Oracle Database in a Large Data Warehouse Clare Somerville,
Clive Cooper		 source 10
SUGI 1998 Programming for Job Security Revisited: Even More Tips and Techniques to Maximize Your Indispensability Arthur L. Carpenter,
Tony Payne		 source 9
SUGI 1998 SAS Program Efficiency for Beginners Bruce F. Gilsen source 9
SUGI 1998 The SET Statement and Beyond: Uses and Abuses of the SET Statement JoAnn R. Matthews source 7
NESUG 1997 SAS Program Efficiency for Beginners Bruce F. Gilsen 9
SESUG 1997 How MERGE Really Works Bob Virgile 8
SUGI 1997 It Takes at Least Two to Tango - A Data Set Joining Primer Caroline C. Bahler source 9
SUGI 1997 Round Pegs Into Square Holes: Data Warehouses for the Hardware Impaired Michael L. Davis source 6
SUGI 1997 SAS Program Efficiency for Beginners Bruce F. Gilsen source 10
SESUG 1996 A SAS Programmer's View of the SAS Supervisor H. Ian Whitlock 11
SESUG 1996 It Takes at Least Two to Tango - A Data Set Joining Primer Caroline Babler 8
NESUG 1996 Doing the Impossible with FSEDIT and AF: How a screen and frame can be Syncronized Richard A. DeVenezia 8
NESUG 1996 Round Pegs Into Square Holes: Data Warehouses for the Hardware Impaired Michael L. Davis 8
NESUG 1996 SAS Program Efficiency for Beginners Bruce F. Gilsen 10
MWSUG 1996 Randomly Accessing Files Using the KEY=Option Kim L. Kolbe Ritzow 10
SUGI 1996 Data Summary: Beyond the Basics Susan J. Slaughter,
Lora D. Delwiche		 source 7
SUGI 1996 Data Transfer between SAS Software and Other PC Software J. Michael Miscisin source 5
SUGI 1996 SAS Program Efficiency for Beginners Bruce F. Gilsen source 10
MWSUG 1995 Efficient Techniques for Random Access to SAS Data Sets David Sommer 6
NESUG 1995 DATA Step Reporting Marge Scerbo 7
NESUG 1995 Let The SET Statement Do Your Record Counting For You Michael A. Walega 2
NESUG 1995 Retrieving Data from Large DB2 Tables Based on Keys in SAS: The Sequel Judy Loren,
Jack N. Shoemaker		 10
NESUG 1995 SAS Program Efficiency for Beginners Bruce F. Gilsen 11
WUSS 1995 Merging a Single Observation with Many Using Multiple SET Statements Lora D. Delwiche,
Susan J. Slaughter		 source 2
SESUG 1995 Code Review of A Macro from Observations H. Ian Whitlock 2
SESUG 1995 Posters To FORMAT or MERGE . ... That Is The Question Caroline C. Bahler 6
SUGI 1995 DATA Step Reporting Marge Scerbo source 7
SUGI 1995 Efficient Techniques for Random Access to SAS Data Sets David Sommer source 6
SUGI 1995 To Merge or Not to Merge: These are the Answers John Badolato source 5
SUGI 1995 Using Indexes for Direct Access to SAS Datasets Judy Loren source 7
WUSS 1994 Speedy Data Retrieval and Display in a SAS/AF System: A Case Study Louise Weiler,
Standish Sibley,
Tim Berryhill		 source 4
WUSS 1994 The Joys of Merging: Alternative Techniques Joan Keesey source 6
NESUG 1994 DATA Step Reporting Marge Scerbo 7
NESUG 1994 Replacing Records in a Data File with the MERGE Statement Charles A. DePascale 1
NESUG 1994 Seeing Double: How to Compare a SAS Dataset with Itself Judy Loren 2
NESUG 1994 Table Lookups in the SAS DATA Step Gary L. Katsanis 7
NESUG 1994 Using Indexes for Direct Access to SAS Datasets Judy Loren 7
MWSUG 1994 A Set of SAS Macros for Producing Customized Reports Greg A. Grandits,
Ken Svendsen		 6
SESUG 1994 Another Sorting Technique for Large, Troublesome Datasets David Hopkins 2
SUGI 1994 A Set of SAS Macros for Producing Customized Reports Greg A. Grandits,
Ken Svendsen		 source 6
SUGI 1994 Keys to the DATA: Using the KEY= Option on the SET Statement Ben Conner source 3
SUGI 1994 Table Lookups in the SAS DATA Step Gary L. Katsanis source 7
SUGI 1994 The Joys of Merging: Alternative Techniques Joan Keesey source 6
NESUG 1993 DATA Step Reporting Marge Scerbo 7
NESUG 1993 Stop The Program, I Want To Get Off! Gary L. Katsanis 1
WUSS 1993 Keys to the DATA: Using the KEY= Option on the SET Statement Ben Conner source 3
SCSUG 1993 Mini-Tips for Maxi-Programmers Jimmy A. DeFoor 22
SCSUG 1993 The SET Statement and Beyond: Uses and Abuses of the SET Statement S. David Riba 7
MWSUG 1993 Efficent Use of Data Storage with SAS Eric Webster 9
MWSUG 1993 The SET Statement and Beyond: Uses and Abuses of the SET Statement S. David Riba 7
SUGI 1993 DATA Step Changes and Enhancements Jeffrey A. Polzin source 6
SUGI 1993 SET, MERGE, UPDATE, or MODIFY? (And What about Indexing?) Phil J. Weiss source 6
SUGI 1993 The SET Statement and Beyond: Uses and Abuses of the SET Statement S. David Riba source 7
SESUG 1993 Three Ways You Can Get Special Data Into the SAS Data Step William S. Calvert 4
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 A Binary Search for Non-Unique Keys Derek Drummond source 5
SUGI 1992 Appeal to a HIER Authority: Graphing CA-7 Scheduling Dependencies Brent Turner source 6
SUGI 1992 Getting It and Keeping It with SAS Software-Advanced Strategies Sally M. Muller,
Kenneth A. Hardy,
Keith J. Brown		 source 7
SUGI 1992 SAS Classes for Nonprogrammers in the Clinical Data Management World Susan V. Hale source 4
SUGI 1992 Spin, Rotate, and View Three-Dimensional Point Clouds: Dynamic Exploration of SAS Data Sets without SAS/INSIGHT "Software Arthur L. Carpenter,
Clinton A. Carpenter		 source 6
SUGI 1992 The SAS System Supervisor - A Version 6 Update Merry G. Rabb,
Donald J. Henderson,
Jeffrey A. Polzin		 source 8
SUGI 1992 Use of the KEEP and DROP Concept in Batch SAS Programs Bill Schallert source 6
NESUG 1991 DATA Step Reporting Marge Scerbo 7
NESUG 1991 Fuzzy Merges (How to Make MERGE Really Work) Jack N. Shoemaker 6
NESUG 1991 Introduction to Efficient Programming Techniques David S. Septoff,
Paige Valentine-Query		 5
MWSUG 1991 Getting Started with TIGER: A Tutorial Gary F. Plazyk 10
SEUGI 1991 Effective Use of Indexes in the SAS System Steve Beatrous source 10
SEUGI 1991 Some New Features in the DATA STEP Sarah Bell source 7
SUGI 1991 An Insider's Sneak Preview of the Next DATA Step Release Jeffrey A. Polzin source 7
SUGI 1991 Effective Use of Indexes in the SAS System Stephen M. Beatrous,
Karen Armstrong		 source 10
SUGI 1991 Manipulating SAS Data Sets: An Introduction Richard Alonso source 6
SUGI 1991 SAS Software Puzzles '91: The Debugging Continues Warren Repole Jr. source 7
SUGI 1991 SAS/ACCESS Interface for IMS: Now You See It, Now You Don't Nancy J. Wills,
Louise M. McCrorie		 source 9
SUGI 1991 The SAS System Supervisor - A Version 6 Update Donald J. Henderson,
Merry G. Rabb,
Jeffrey A. Polzin		 source
SUGI 1991 The SAS System: Interface to DEC'"'s Common Data Dictionary Ken D. Worsham source 6
SUGI 1991 Using SAS Software to Assess Factors Affecting Employee Attitudes and Turnover in Temporary Offices Mark Holdrege,
John Cunningham		 source 6
SUGI 1991 Using the Concurrency Engine Effectively under VMS Darylene Hecht source 5
NESUG 1990 Efficiency Techniques for Improving I/O and Processing Time in the DATA Step Neil H. Howard 9
NESUG 1990 Efficient SAS Software Programming: A New Synthesis Jean Hardy 8
NESUG 1990 How MERGE Really Works Robert Virgile 7
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
SEUGI 1990 Using Relational Databases (ORACLE and RD) Together with the SAS System on VMS Thomas J. R. Emmerich source 5
SUGI 1990 Easier User Interface with SET and MERGE Macros Cheryl C. Hammond-Puhi source 2
SUGI 1990 Gracefully Handling Empty Files in the SAS System Matt Kleinosky,
Orion V. Hanger		 source 4
SUGI 1990 Mortar and Bricks: Using Basic SAS System Procedures to Manipulate Your Data Peter Kretzman source 8
SUGI 1990 Overview of the SET, UPDATE, AND MERGE Statements Richard Alonso source 5
SUGI 1990 The SAS Supervisor - A Version 6 Update Donald J. Henderson,
Merry G. Rabb,
Jeffrey A. Polzin		 source 9
SUGI 1990 Using Relational Database Technology and the SAS System to Develop SAS' System Applications under the VMS "Operating System Jean Moorefield source 7
NESUG 1989 Advanced SET and MERGE Processing Robina G. Thornton,
Merry G. Rabb		 11
NESUG 1989 Efficiency Techniques for Improving I/O and Processing Time in the DATA Step Neil H. Howard 6
NESUG 1989 The SAS Supervisor Donald J. Henderson 7
SEUGI 1989 Using The New SQL Procedure In SAS Programs Paul Kent source 6
SUGI 1989 A Meta-database Implementation Strategy for Documentation and Retrieval Using the SAS System John Podgurski source 10
SUGI 1989 The SAS Supervisor and SET/MERGE Processing Aiman M. Zeid source 10
NESUG 1988 Advanced SET and MERGE Processing Robina G. Thornton,
Merry G. Rabb		 14
NESUG 1988 Efficiency Techniques for Improving I/O and Processing Time in the DATA Step Neil H. Howard 14
NESUG 1988 Efficient Use of Table Lookup Procedures Craig K. Ray,
Howard Levine		 15
NESUG 1988 The SAS Supervisor Donald J. Henderson,
Merry G. Rabb		 pdf 16
SUGI 1988 Advanced SET and MERGE Processing Robina G. Thornton,
Merry G. Rabb		 source 10
SUGI 1988 Cutting Costs in the DATA Step: Efficiency Techniques for Improving I/O and Processing Time Neil H. Howard source 6
SUGI 1988 Efficient Programming with the SAS System for Personal Computers: Save Time, Save Space Lisa Ann Horwitz,
E. Tim Thompson		 source 6
SUGI 1988 Efficient Use of a SAS Data Library as a Pseudo-relational Data Base Vladimir Svirsky source 6
SUGI 1988 Processing Large Files: The SUMMARY Procedure and Other Efficiency Tips Juliana M. Ma source 9
SUGI 1988 The SAS Supervisor Donald J. Henderson,
Merry G. Rabb		 source 7
SUGI 1988 UNI-PRO: A System to Screen Large Health Care Data Sets Using the SAS System William J. McDonald,
J. Jon Veloski		 source 6
SUGI 1987 Sampling with SAS Software: A Macro for Drawing PPS Samples Eleanor M. Dillon,
James E. Smith		 source 5
SUGI 1987 The SAS Supervisor Donald J. Henderson,
Merry G. Rabb		 source 10
SEUGI 1986 SAS/SHARE Software: Concurrent Update of SAS Data Libraries Jack Wallace source 9
SUGI 1986 Efficient Use of Table Lookup Procedures Howard Levine,
Craig K. Ray		 source 6
SUGI 1986 Improving Binary Search Techniques Robert Virgile source 6
SUGI 1986 SAS/SHARE Software: Concurrent Update of SAS Data Libraries Jack Wallace source 9
SUGI 1984 Efficient Data Retrieval-Direct Access Using the Point Option Neil H. Howard,
Linda Williams Pickle		 source 5
SUGI 1983 Efficient Techniques for Large Data Files Judith H. Mopsik source
SUGI 1982 Improving the Data Management Expertise of Experienced SAS Users Joshua Sharlin source 6
SUGI 1982 Selecting Subset of Data Donald J. Henderson source
SUGI 1982 Set Merge and Update Peter L. Rikard source 4
SUGI 1982 Techniques for Interrelating and Reducing Data Bases Using SAS Robert U. Anderson,
James W. Davis,
Steven Flint		 source
SUGI 1982 Unconventional Merges Peter L. Rikard source 3

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