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287 papers and 4 presentations; 226 titles.

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Conference × Year × Title × Authors Extras Pages
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 Slamming Datasets Together, Without Hurt, Using SAS, R and Excel David W. Franklin source 6
SESUG 2024 Advanced DATA Step Look-Back and Look-Ahead Techniques Joshua M. Horstman source 5
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
WUSS 2023 Open-Source Essentials HOW - R and RStudio Wendy Christensen source 17
SESUG 2023 How to Merge SAS Datasets with PII Julie Plano,
Keli Sorrentino		 source 6
PharmaSUG 2023 A Macro to Identify Repeating SAS BY Variables in a MERGE Timothy J. Harrington source 9
SESUG 2022 Offensive Programming: A Threesome of Error-Throwing Macros Quentin McMullen source 20
WUSS 2022 Hash Tables Like You've Never Seen Them Before [presentation] Mathieu Gaoette source 31
PharmaSUG 2022 Look Up Not Down: Advanced Table Lookups in Base SAS Jayanth Iyengar,
Joshua M. Horstman		 source 28
PHUSE US 2022 Incorporating Immunogenicity Data from Various Analyzing Labs [presentation] Elisabeth van Son-Palmen,
Gunasekaran Subramaniam		 source 19
PharmaSUG 2021 Mashing Two Datasets Together David W. Franklin source 5
SESUG 2020 Log the SAS Log Analyzer for Audit Amarnath Vijayarangan source 6
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 Urge to MERGE? Maybe You Should UPDATE Instead Ben Cochran source 7
SESUG 2019 Exploring Efficiency in Data Manipulation with SAS: How to Get the Most Out of My Software and Hardware Jonathan W. Duggins source 10
SESUG 2019 You're Doing It Wrong! Volume 002 Shane Rosanbalm source 7
MWSUG 2019 Look Up Not Down: Advanced Table Lookups in Base SAS Jayanth Iyengar,
Joshua M. Horstman		 24
MWSUG 2019 Urge to MERGE? Maybe You Should UPDATE Instead Ben Cochran 8
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
SGF 2019 DOSUBL Function + SQL View + Hash Object = FedSQL + PROC DS2 Hash Package Yutaka Morioka,
Jun Hasegawa		 source 10
SGF 2019 Interaction between SAS and Python for Data Handling and Visualization Yohei Takanami source 22
SCSUG 2018 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman source 16
MWSUG 2018 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman 16
PharmaSUG 2018 Beyond MERGE for Combining Datasets David W. Franklin source 4
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
SGF 2018 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman source 16
SGF 2018 Run-Time Validation of SAS Jobs: A Threesome of Error-Throwing Macros Quentin McMullen source 18
SESUG 2017 Beginner Beware: Hidden Hazards in SAS Coding Alissa Wise source 7
SESUG 2017 Leads and Lags: Static and Dynamic Queues in the SAS DATA STEP, 2nd ed. Mark Keintz source 15
SESUG 2017 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman source 14
SCSUG 2017 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski source 10
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 Cleaning Messy Data: SAS Techniques to Homogenize Tax Payment Data Aaron Barker 8
MWSUG 2017 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman 14
MWSUG 2017 The Building Blocks of SAS Datasets - S-M-U (Set, Merge, and Update) Andrew T. Kuligowski 13
WUSS 2017 Five Ways to Flip-Flop Your Data Joshua M. Horstman source 10
WUSS 2017 Introduction to DATA Step Programming: SAS Basics II Susan J. Slaughter 39
WUSS 2017 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman source 14
PharmaSUG 2017 Hashtag #Efficiency! An Exploration of Hash Tables and Other Techniques Lakshmi Nirmala Bavirisetty,
Kaushal Chaudhary,
Deanna Naomi Schreiber-Gregory		 source 9
PharmaSUG 2017 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman source 10
PharmaSUG 2017 Power of Interleaving and RETAIN Combination in Data Manipulation Zongming Pan source 10
SGF 2017 Data Validation Using the SAS SORT Procedure and MERGE Statement Barry Frye source 11
SGF 2017 Leads and Lags: Static and Dynamic Queues in the SAS DATA STEP, 2nd ed. Mark Keintz source 15
SCSUG 2016 Anatomy of a Merge Gone Wrong Joshua M. Horstman source 5
SESUG 2016 Universal File Flattener David A. Vandenbroucke source 12
PHUSE EU 2016 How Well Can you Speak SAS or is What you See What you Get? Bahatska Yuliia source 7
MWSUG 2016 Anatomy of a Merge Gone Wrong Joshua M. Horstman 5
MWSUG 2016 Hashtag #Efficiency! An Introduction to Hash Tables Lakshmi Nirmala Bavirisetty,
Deanna Naomi Schreiber-Gregory,
Kaushal Chaudhary		 10
PharmaSUG 2016 Log Checks Made Easy Yogesh Pande source 4
SGF 2016 Four Lines of Code: Using Merge and Colons to Construct Historical Data from Status Tables Jingyu She source 2
SGF 2016 The Three I's of SAS Log Messages, IMPORTANT, INTERESTING, and IRRELEVANT William E. Benjamin Jr. source
zip		 21
SGF 2016 Uncommon Techniques for Common Variables Christopher J. Bost source 10
SGF 2016 Universal File Flattener David A. Vandenbroucke source
zip		 15
MWSUG 2015 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski 10
MWSUG 2015 Table Lookup Techniques: From the Basics to the Innovative Arthur L. Carpenter 11
SESUG 2015 Ouch, How did that get there? The pitfalls of merging. Nancy McGarry source 3
WUSS 2015 DATA Step Merging Techniques: From Basic to Innovative Arthur L. Carpenter source 12
WUSS 2015 S-M-U (Set, Merge, and Update) Revisited Andrew T. Kuligowski source 13
PharmaSUG CN 2015 Not Just Merge - Complex Derivation Made Easy by Hash Object Lu Zhang 5
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 Not Just Merge - Complex Derivation Made Easy by Hash Object Lu Zhang source 5
SGF 2015 Anatomy of a Merge Gone Wrong Joshua M. Horstman source 5
SGF 2015 Inside the DATA Step: Pearls of Wisdom for the Novice SAS Programmer Joshua M. Horstman,
Britney D. Gilbert		 source 11
SGF 2015 S-M-U (Set, Merge, and Update) Revisited Andrew T. Kuligowski source 13
SGF 2015 Table Lookup Techniques: From the Basics to the Innovative Arthur L. Carpenter source 11
SESUG 2014 Hidden in plain sight: my top ten underpublicized enhancements in SAS Versions 9.2 and 9.3 Bruce F. Gilsen source 12
MWSUG 2014 DATA Step Merging Techniques: From Basic to Innovative Arthur L. Carpenter 11
MWSUG 2014 Five Ways to Flip-Flop Your Data Joshua M. Horstman 9
MWSUG 2014 Ignorance is Not Bliss: Pearls of Wisdom for the Novice SAS Programmer Joshua M. Horstman,
Britney D. Gilbert		 9
WUSS 2014 SAS Essentials II (or How to Train Your SAS Data Sets) Tasha Chapman source 12
WUSS 2014 Table Lookup Techniques: From the Basics to the Innovative Arthur L. Carpenter source 11
PharmaSUG 2014 Five Ways to Flip-Flop Your Data Joshua M. Horstman source 9
PharmaSUG 2014 MACUMBA - The log belongs to the program Michael Weiss source 8
PharmaSUG 2014 Table Lookup Techniques: From the Basics to the Innovative Arthur L. Carpenter source 11
SGF 2014 DATA Step Merging Techniques: From Basic to Innovative Arthur L. Carpenter source 10
SGF 2014 Five Ways to Flip-Flop Your Data Joshua M. Horstman source 9
PHUSE EU 2013 Macro to Conduct Consistency Checks [presentation] Johanna Gaignard,
Walter H. Hufford Jr.		 source 10
PHUSE EU 2013 Mission Possible: Your Assignment is to Validate Output for a Study Susan Fehrer Coulson source
presentation source		 7
MWSUG 2013 Anatomy of a Merge Gone Wrong James Lew,
Joshua M. Horstman		 5
NESUG 2013 Hidden in plain sight: my top ten underpublicized enhancements in SAS Versions 9.2 and 9.3 Bruce F. Gilsen 12
NESUG 2013 Ouch, how did that get here? The pitfalls of merging ... [presentation] Nancy McGarry 10
PharmaSUG 2013 Anatomy of a Merge Gone Wrong James Lew,
Joshua M. Horstman		 source 5
PharmaSUG 2013 Mission Possible: Your Assignment is to Validate Output for a Study Susan Fehrer Coulson,
Kevin R. Coulson		 source 7
PharmaSUG 2013 SQL, HASH Tables, FORMAT and KEY= - More Than One Way to Merge Two Datasets David W. Franklin source 5
SGF 2013 A Day in the Life of Data - Part 2 Harry Droogendyk source 13
SGF 2013 Data Merging and Visualization to Identify Associations Between Environmental Factors and Disease Outbreaks Azhar Nizam,
Neeta Shenvi,
Xin Zhang		 source 12
MWSUG 2012 Avoiding Pitfalls when Merging Data James Lew,
Joshua M. Horstman		 5
MWSUG 2012 New Vs. Old - Under the Hood with Procs CONTENTS and COMPARE Patricia Hettinger 12
WUSS 2012 Countdown of the Top 10 Ways to Merge Data David W. Franklin source 6
PharmaSUG 2012 "Analysis-ready" - Considerations, Implementations, and Real World Applications Ellen (Zihui) Lin,
Beiying Ding		 source 6
SGF 2012 Good Programming Practices: Creating Robust Programs Gregory S. Barnes Nelson,
Jay Zhou		 source 16
SCSUG 2011 The Top 10 Head Scratchers: SAS Log Messages That Prompt a Call to SAS Technical Support Kim M. Wilson source 9
SESUG 2011 Analyst Beware: Five Dangerous Data Step Coding Traps David H. Abbott source 9
MWSUG 2011 Who are You? Use of Soundex and Merge to Cross-Walk one Dataset to Another Misty Johnson 7
NESUG 2011 PROC FORMAT - Not Just Another Pretty Face Lois Levin 13
NESUG 2011 SAS DATA Step Merge - A Powerful Tool Dalia C. Kahane 13
NESUG 2011 The Top 10 Head Scratchers: SAS Log Messages That Prompt a Call to SAS Technical Support Kim M. Wilson 9
PharmaSUG 2011 Create a Format from a SAS Data Set Ruth Marisol Rivera source 7
PharmaSUG 2011 Good Programming Practices in Healthcare Creating Robust Programs Gregory S. Barnes Nelson,
Jay Zhou		 source 17
SGF 2011 The Top 10 Head Scratchers: SAS Log Messages That Prompt a Call to SAS Technical Support Kim M. Wilson source 9
NESUG 2010 How to Think Through the SAS DATA Step H. Ian Whitlock 17
NESUG 2010 LOG CHECKING: What to check and why? Sridhar R. Dodlapati,
Kiran K. Karidi,
Mahipal R. Vanam		 5
SCSUG 2010 Beyond the Simple Merge in SAS Vanessa Cox source 6
WUSS 2010 The Building Blocks of SAS Datasets - S-M-U (Set, Merge, and Update) Andrew T. Kuligowski source 13
SESUG 2010 Merging into Hash: Some Practical Examples of Converting MERGE Statements into Hash Objects Ying Liu source 23
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 SAS Code Validation: L.E.T.O. Method Aaron J. Augustine source 12
PHUSE EU 2009 The Perfect Match - an appreciation of the functionality of the dataset MERGE Diana Stuart source 5
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
PNWSUG 2009 Multiple Set Statements in a Data Step: A Powerful Technique for Combining and Aggregating Complex Data Renu Gehring 11
NESUG 2009 9 Ways to Join Two Datasets David W. Franklin 6
NESUG 2009 Don't Despair, You Do Have An Option! Wei (Lisa) Lin,
Jiannan Kang		 13
NESUG 2009 Please don't Merge without By !! Monal Kohli 11
NESUG 2009 The Building Blocks of SAS Datasets - S-M-U (Set, Merge, and Update) Andrew T. Kuligowski 13
NESUG 2009 Using DATA STEP MERGE and PROC SQL JOIN to Combine SAS Datasets Dalia C. Kahane 15
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
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 Merging Data Eight Different Ways David W. Franklin source 5
SGF 2009 MERGING vs. JOINING: Comparing the DATA Step with SQL Malachy J. Foley source 17
SGF 2009 The Perils of End-of-File Processing When Subsetting Data Leonard E. Landry source 7
WUSS 2008 The Power of the BY Statement Toby Dunn,
Paul A. Choate		 source 16
SESUG 2008 Joins: How to Put it All Together Janet E. Stuelpner source 10
SESUG 2008 NOTEs in a SASLOG : Of LOST CARDs and MERGE Statements with Repeats of By Values Andrew T. Kuligowski source 14
SESUG 2008 SET, MERGE and beyond. Erik W. Tilanus source 15
SESUG 2008 The Art of Debugging H. Ian Whitlock source 20
NESUG 2008 HELP! - My MERGE Statement Has More Than One Data Set With Repeats of BY Values! Andrew T. Kuligowski 5
NESUG 2008 Merging Data Seven Different Ways David W. Franklin 4
NESUG 2008 Using DATA STEP MERGE and PROC SQL JOIN to Combine SAS Datasets Dalia C. Kahane 15
SGF 2008 Many-to-Many Merges in the DATA Step Edward Heaton source 9
SGF 2008 SET, MERGE and beyond. Erik W. Tilanus source 15
SGF 2008 The Art of Debugging H. Ian Whitlock source 20
SGF 2008 Using Table Lookup Techniques Efficiently Linda T. Jolley,
Jane Stroupe		 source 11
NESUG 2007 Measuring Days and Hours: An Introduction to the Handy Uses of the IN, END, LAG, FIRST and LAST Statements Catherine Loveless-Schmitt 9
NESUG 2007 Partially Transforming Hierarchical Data Sets for Sequential Processing Using Arrays Richard L. Downs Jr.,
Pura A. Perez		 9
NESUG 2007 The Power and the Trap of Automatic Retain Yunchao (Susan) Tian 6
MWSUG 2007 Getting Started with the DATA Step Hash Object Jason Secosky,
Janice Bloom		 9
WUSS 2007 Automating the SORT-SORT-MERGE and Overcoming the Many to Many MERGE: %ProcMerge Carter Sevick source 17
WUSS 2007 The Power of the BY Statement Toby Dunn,
Paul A. Choate		 source 16
SCSUG 2007 The Power of the BY Statement Toby Dunn,
Paul A. Choate		 11
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 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 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
MWSUG 2006 Accuracy or Efficiency in Merging Cindy Liu 6
MWSUG 2006 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski 10
SCSUG 2006 Getting Started with the DATA Step Hash Object Jason Secosky,
Janice Bloom		 10
SCSUG 2006 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski 10
PHUSE EU 2006 Defensive Programming Techniques Jennie McGuirk,
John Woods		 source 5
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
SUGI 2006 A Hands-On Introduction to SAS Basics and the SAS Display Manager Debbie Buck - SC source 12
SUGI 2006 How to Think Through the SAS DATA Step H. Ian Whitlock source 20
PNWSUG 2005 Table Lookups: From IF-THEN to Key-Indexing Arthur L. Carpenter 10
SESUG 2005 _05 Managing a Many to Many Merge using Formats, Direct Access, and Implied Hashing source 8
SESUG 2005 How SAS Thinks Neil H. Howard source 19
SESUG 2005 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski source 10
SCSUG 2005 MERGING vs. JOINING: Comparing the DATA Step with SQL Malachy J. Foley 17
MWSUG 2005 MERGING vs. JOINING: Comparing the DATA Step with SQL Malachy J. Foley 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 How SAS Thinks Neil H. Howard 19
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 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 Merging versus Joining: Comparing the DATA Step with SQL Malachy J. Foley source 18
SUGI 2005 PROC FORMAT - Not Just Another Pretty Face Lois Levin source 12
SUGI 2005 Slicing and Dicing the SAS Data Set William C. Murphy source 5
NESUG 2004 Danger: MERGE Ahead! Warning: BY Variable with Multiple Lengths! Robert Virgile 6
NESUG 2004 How SAS Thinks or Why the DATA Step Does What It Does Neil H. Howard 19
NESUG 2004 PROC FORMAT - Not Just Another Pretty Face Lois Levin 11
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 Merging: Avoid the Cones Jessica Bonow,
Little Rock		 source 5
SESUG 2004 SAS System Options Are Your Friends Edward Heaton source 15
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
PNWSUG 2004 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski 11
SUGI 2004 How to Incorporate Old SAS Data into a New DATA Step, or "What is S-M-U?" Andrew T. Kuligowski source 14
WUSS 2003 Merging Large Internet And Paper Survey Datasets For A 22-Year Longitudinal Cohort Study Thomas E Corbeil,
Tyler C. Smith,
Besa Smith,
Margaret A. K. Ryan		 source 5
WUSS 2003 Table Lookups: From IF-THEN to Key-Indexing Arthur L. Carpenter source 7
SCSUG 2003 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski 11
SESUG 2003 A Sampler of Code Techniques H. Ian Whitlock source 6
SESUG 2003 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski source 10
NESUG 2003 Danger: MERGE Ahead! Warning: BY Variable with Multiple Lengths! Robert Virgile 6
PharmaSUG 2003 Danger: MERGE Ahead! Warning: BY Variable with Multiple Lengths! Bob Virgile 6
PharmaSUG 2003 SQL for People Who Don't Think They Need SQL Erin M. Christen 8
SUGI 2003 Danger: MERGE Ahead! Warning: BY Variable with Multiple Lengths! Bob Virgile Danger source 6
SCSUG 2002 MERGING: Comparing the DATA Step with SQL Malachy J. Foley 11
NESUG 2002 Debugging 101 Peter Knapp 10
NESUG 2002 To Err Is Human; to Debug, Divine Roger Staum 11
PharmaSUG 2002 To Err Is Human; To Debug Devine Roger Staum 12
SUGI 2002 Many-to-Many Merging Using the SAS Macro Facility Jonathan D. Mahnken source 6
SUGI 2002 To Err Is Human; to Debug, Divine Roger Staum source 11
MWSUG 2001 50 Ways To Merge Your Data - Installment 1 Kristie Schuster,
Lori L. Sipe		 6
MWSUG 2001 Table Lookups: From IF-THEN to Key-Indexing Arthur L. Carpenter 8
WUSS 2001 Table Lookups: From IF-THEN to Key-Indexing Arthur L. Carpenter source 8
SESUG 2001 Point, Set, Match (Merge) - A Beginner's Lesson Jennifer Hoff Lindquist source 8
SUGI 2001 50 Ways To Merge Your Data - Installment 1 Kristie L. Schuster,
Lori L. Sipe		 source 5
SCSUG 2000 Many-to-Many Matching Using the Inner Join Thomas J. Winn Jr. 3
SCSUG 2000 Merge Processing - Alternative Table Lookup Techniques Destiny Corporation (a company) 7
NESUG 2000 Merge Processing - Alternative Table Lookup Techniques Destiny Corporation (a company) 8
NESUG 2000 Partially Transforming Hierarchical Data Sets for Sequential Processing Using Arrays Richard L. Downs Jr.,
Pura A. Perez		 8
WUSS 2000 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski source 5
WUSS 2000 Simplifying a Merge with SAS Macro S. Patrick Thornton source 5
PharmaSUG 2000 How MERGE Really Works Bob Virgile 12
SUGI 2000 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski source 5
SESUG 1999 Hiring the Best SAS Programmers Neil H. Howard source 10
SESUG 1999 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski source 8
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 One Efficient Way to Select Records From a Very Large Flat File or SAS Data Set George Bukhbinder 2
SUGI 1999 A Simple Framework for Sequentially Processing Hierarchical Data Sets for Large Surveys Richard L. Downs Jr.,
Pura A. Perez		 source 6
NESUG 1998 Table Look-up using Indexes, SQL, Arrays, and Formats without using Match-Merge Data Steps Sandra Lynn Aker 7
SESUG 1998 A Simple Framework for Sequentially Processing Hierarchical Data Sets for Large Surveys Richard L. Downs Jr.,
Pura A. Perez		 10
SESUG 1998 MATCH-MERGING: 27 Plus Traps and How to Avoid Them Malachy J. Foley 10
SESUG 1998 PC Hands-On Workshops Destiny Corporation (a company) 7
SUGI 1998 Creating a Flexible Parameter Driven Reporting Program Using Global Variables Karen Dudley source 3
SUGI 1998 MATCH-MERGIN G : 20 Some T raps and How to Avoid Them Malachy J. Foley source 21
SUGI 1998 Overall Part Number Item Rank Rank source 19
SUGI 1998 Understanding Indexed Datasets and Using Direct Access Queries John Charles Gober source
WUSS 1997 Create a Flexible Parameter Driven Reporting Program By Using Global Variables and PROC REPORT Karen Dudley source 4
WUSS 1997 Data Collection: An Internet Based Approach Aradhana Gokul Janga source 6
WUSS 1997 The Problem with NODUPS Jack Hamilton source 4
MWSUG 1997 Table Look-up using Indexes, Arrays, Formats, and SQL without using Matched Merge Data Steps Sandra Lynn Aker 7
SESUG 1997 How MERGE Really Works Bob Virgile 8
PharmaSUG 1997 MATCH-MERGING: Techniques, Tricks, and Traps Malachy J. Foley 8
SUGI 1997 Advanced MATCH-MERGING: Techniques, Tricks, and Traps Malachy J. Foley source 8
SUGI 1997 Advanced MATCH-MERGING: Techniques, Tricks, and Traps Malachy J. Foley source 8
SUGI 1997 It Takes at Least Two to Tango - A Data Set Joining Primer Caroline C. Bahler source 9
SESUG 1996 It Takes at Least Two to Tango - A Data Set Joining Primer Caroline Babler 8
SESUG 1996 MATCH-MERGING: Techniques, Tricks, and Traps Malachy J. Foley 8
SESUG 1996 NO MORE MERGE - Alternative Table Lookup Techniques Dana Rafiee 6
SESUG 1996 Software Validation and Testing Andrew T. Kuligowski 9
NESUG 1996 The Fuzzy Feeling SAS Provides: Electronic Matching of Records without Common Keys Charles Partridge 9
MWSUG 1996 NO MORE MERGE - Alternative Table Lookup Techniques Dana Rafiee 6
MWSUG 1996 Randomly Accessing Files Using the KEY=Option Kim L. Kolbe Ritzow 10
WUSS 1996 Tips and Techniques for Updating a Repository Data Warehouse Ty Lee source 6
SUGI 1996 JOining Strategies Access to All Data Caroline C. Bahler,
Stephen Clos		 source 5
SUGI 1996 NO MORE MERGE - Alternative Table Lookup Techniques Dana Rafiee source 6
SUGI 1996 Software Validation and Testing Andrew T. Kuligowski source 9
SUGI 1996 Tips and Techniques for Data Fixes in a Repository Data Warehouse Ty Lee source 6
MWSUG 1995 Joining Data with SQL Kim L. Kolbe Ritzow 6
NESUG 1995 Getting the Most from the SAS LOG Robert G. Hall 4
SESUG 1995 Posters To FORMAT or MERGE . ... That Is The Question Caroline C. Bahler 6
SEUGI 1995 The Importance of IN Anders Skollermo source 11
SUGI 1995 Fuzzy Joins using SOL Jack N. Shoemaker source 10
SUGI 1995 To Merge or Not to Merge: These are the Answers John Badolato source 5
NESUG 1994 Fuzzy Joins Using SQL Jack N. Shoemaker 10
NESUG 1994 How MERGE Really Works Bob Virgile 8
NESUG 1994 Replacing Records in a Data File with the MERGE Statement Charles A. DePascale 1
NESUG 1994 Stop Merging and Start Combining Robert C. Nicol 5
SUGI 1994 Getting the Most from the SAS LOG Robert G. Hall,
Judith H. Mopsik		 source 6
SCSUG 1993 Mini-Tips for Maxi-Programmers Jimmy A. DeFoor 22
SUGI 1993 Techniques for Merging Non-Indexed Data Sets with Duplicate Values of the BY Variables Mark Prior source 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
SUGI 1992 SAS Classes for Nonprogrammers in the Clinical Data Management World Susan V. Hale source 4
SUGI 1992 The SAS System Supervisor - A Version 6 Update Merry G. Rabb,
Donald J. Henderson,
Jeffrey A. Polzin		 source 8
NESUG 1991 Fuzzy Merges (How to Make MERGE Really Work) Jack N. Shoemaker 6
MWSUG 1991 Enhancing the Multipl Match-Merge Solution Bill Horman 5
SUGI 1991 Manipulating SAS Data Sets: An Introduction Richard Alonso source 6
SUGI 1991 The SAS System Supervisor - A Version 6 Update Donald J. Henderson,
Merry G. Rabb,
Jeffrey A. Polzin		 source
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
SUGI 1990 Organizing CMS Files Using the SORT Procedure, REXX, and FILELIST Kimberly J. LeBouton source 5
SUGI 1990 The SAS Supervisor - A Version 6 Update Donald J. Henderson,
Merry G. Rabb,
Jeffrey A. Polzin		 source 9
NESUG 1989 Advanced SET and MERGE Processing Robina G. Thornton,
Merry G. Rabb		 11
NESUG 1989 The SAS Supervisor Donald J. Henderson 7
SUGI 1989 A Meta-database Implementation Strategy for Documentation and Retrieval Using the SAS System John Podgurski source 10
NESUG 1988 Advanced SET and MERGE Processing Robina G. Thornton,
Merry G. Rabb		 14
NESUG 1988 The SAS Supervisor Donald J. Henderson,
Merry G. Rabb		 pdf 16
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
SUGI 1984 A Generalized Interactive Full Screen Edit-Update System Using SAS Software Jesse Gary,
Donald J. Henderson,
Connie G. Welch		 source 6
SUGI 1984 Panel Discussion John C. Boling,
Mason B. Nichols		 source 17
SUGI 1984 The SAS System as an Information Center Tool Patrick R. Timmins source
SUGI 1982 SD/SDM, a System Design and StatidDynamic Modeling Tool Set Armen Gabrielian source 6

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