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114 papers and 3 presentations; 107 titles.

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Conference × Year × Title × Authors Extras Pages
PHUSE US 2026 Methods of a Fully Automated CONSORT Diagram Macro %CONSORT Jeffrey P. Meyers source
presentation source		 18
PHUSE EU 2025 Close Encounters with Real-World Data Jeffrey M. Abolafia,
Sarah Ferko,
Ingeborg Holt		 source
presentation source		 21
SESUG 2025 Five Easy Ways to Make Your SAS Code Run Faster Mark L. Jordan 18
SESUG 2025 Fuzzy Matching with SAS PROC SQL Mark L. Jordan 16
PharmaSUG 2025 The Model Maketh the Metadata Carlo Radovsky source 19
PHUSE US 2025 Biomedical Concepts: What Are They and Why Should I Care? Stuart Malcolm source
presentation source		 7
PHUSE EU 2024 Leveraging Shiny Modules for Modular and Scalable Web Applications for Clinical Trials/Research Sohan Lal,
Pinku Hooda		 source
presentation source		 10
PHUSE EU 2024 Working with Omics data - A Statistical Programmers perspective Adrian Czaban source
presentation source		 10
PharmaSUG 2024 The Art of Defensive SAS Programming Philip R. Holland source 28
PHUSE US 2024 USUBJID Challenges: Representing Multiple Participations for Analysis and Reporting Emily Bernstein-Hanlon,
Sirisha Davuluri		 source
presentation source		 9
PHUSE EU 2023 Handling Multiple Screenings Using the New Domain DC (Demographics for Multiple Participations) at Merck - Implementation of a New Mapping Process [presentation] Kristina Zweier source 21
PharmaSUG 2023 Methods of a Fully Automated CONSORT Diagram Macro %CONSORT Jeffrey P. Meyers source 21
PHUSE US 2023 Use R to Track and Highlight the Changes Between 2 Versions of Data to Have More Efficient Data Review Disheng Huang,
Kevin Li		 source
presentation source		 5
PHUSE EU 2022 Shiny-tise Your PROC COMPAREs: An Interactive Shiny Application for Data Review and Comparisons [presentation] Paul Jenkins source
video		 34
SGF 2021 Methods of a Fully Automated CONSORT Diagram Macro %CONSORT Jeffrey P. Meyers source
sas
txt
presentation		 20
SGF 2020 Better Student Application Reporting: A Slowly Changing Dimension and SAS Data Integration Studio Lauren E. Schoenheit,
Alexander K. Fantroy		 source 11
SGF 2020 Bits and Bytes - A Mix for High Volumes of Data Karine Désilets source 19
PHUSE EU 2019 Building a F.A.I.R. Foundation for Pharma: The PHUSE GoingTWLD Project Tim P. Williams,
Armando Oliva		 source
presentation source		 5
PHUSE EU 2019 Considerations When Representing Multiple Subject Enrollments in SDTM Kristin Kelly,
Blue Bell		 source
presentation source		 7
SESUG 2019 Analyzing Hospital Medicare Cost Report Data Using SAS - Updated with Output Kimberly Andrews source 19
SESUG 2019 Making Life Easier on the SAS End: Best Practices for Collecting Survey Data Collecting Survey source 11
PharmaSUG 2019 Considerations When Representing Multiple Subject Enrollments in SDTM Kristin Kelly,
Mike Hamidi		 source 8
PharmaSUG 2019 The Art of Defensive Programming: Coping with Unseen Data Philip R. Holland source 8
SGF 2019 Capture-Recapture Databases for Data for Good Projects David J. Corliss source 10
SGF 2019 Making Life Easier on the SAS End: Best Practices for Collecting Survey Data Julie Plano,
Keli Sorrentino		 source 11
PHUSE US 2019 Building SQL Scripts Using Google Sheets R and R Shiny Huiming Tu source
presentation source		 19
PHUSE US 2019 Considerations When Representing Multiple Subject Enrollments in SDTM Kristin Kelly source
presentation source		 6
PHUSE US 2019 Organize and Report Your Clinical Data Today! Michael Litzsinger source
presentation source		 7
PHUSE EU 2018 Developing an End-to-End Standard and Automated Risk-based Monitoring Process Giuseppe Di Monaco,
Tim P. Williams		 source
presentation source		 11
PHUSE EU 2018 Overcoming Resistance to Technology Change: A Linked Data Perspective Tim P. Williams source
presentation source		 8
SESUG 2018 Analyzing Hospital Medicare Cost Report Data Using SAS Kimberly Andrews source 19
PharmaSUG 2018 Automate Clinical Trial Data Issue Checking and Tracking Krishna Avula,
Dale LeSueur		 source 5
SGF 2018 Leverage Custom Geographical Polygons in SAS Visual Analytics Murali Nori,
Falko Schulz		 source 19
SGF 2018 The Art of Defensive Programming Philip R. Holland source 9
MWSUG 2017 Cleaning Messy Data: SAS Techniques to Homogenize Tax Payment Data Aaron Barker 8
SGF 2017 Fighting Crime in Real Time with SAS Visual Scenario Designer John Shipway source 11
SCSUG 2016 %EventChart: A Macro to Visualize Data with Multiple Timed Events Andrew Peng source 6
SGF 2016 Tips and Techniques for Using Site-Signed HTTPS with SAS 9.4 Stuart J. Rogers source 20
SGF 2016 Using the SAS Hash Object with Duplicate Key Entries Paul M. Dorfman source
zip		 16
SESUG 2015 Using the SAS Hash Object with Duplicate Key Entries Paul M. Dorfman source 16
PharmaSUG CN 2015 Not Just Merge - Complex Derivation Made Easy by Hash Object Lu Zhang 5
PharmaSUG 2015 Not Just Merge - Complex Derivation Made Easy by Hash Object Lu Zhang source 5
SGF 2015 Building Credit Modeling Dashboards [presentation] Jeremy D'Antoni source 7
SESUG 2014 Analysis of Zero Inflated Longitudinal Data Using Proc NLMIXED Delia C Voronca,
Leonard E Egede,
Mulugeta Gebregziabher,
Ralph H. Johnson		 source 18
WUSS 2014 Fuzzy Bootstrap Matching Dale Harrington source 9
WUSS 2014 The SAS Hash Object in Action Paul M. Dorfman source 29
PharmaSUG 2014 Creating Define-XML version 2 with the SAS Clinical Standards Toolkit 1.6 Lex Jansen source 33
SGF 2014 Let SAS Power Your .NET GUI Matthew Duchnowski source 10
PharmaSUG 2013 Effective Independent Validation: Tips to Improve the Independent Validation Process Daniel Butner,
Brandon Graham		 source 6
PHUSE EU 2012 Mapping the Company's Legacy Data Model to SDTM Anja Feuerbacher,
Bruce Rogers		 source
presentation source		 7
PharmaSUG 2012 Scrambling of Un-Blinded Data without 'Scrambling Data Integrity'! Jaya Baviskar source 8
SGF 2012 Selecting Unrestricted and Simple Random With Replacement Samples Using Base SAS and PROC SURVEYSELECT David D. Chapman source 14
MWSUG 2011 Dealing with Duplicates in Your Data Joshua M. Horstman,
Roger D. Muller		 7
SGF 2011 HIPAA Compliance: Meeting Privacy Requirements in Combining Multiple Data Sets Using SAS Functions Siew Ching Ang,
Paul M. Darden		 source 12
SESUG 2010 Merging into Hash: Some Practical Examples of Converting MERGE Statements into Hash Objects Ying Liu source 23
PharmaSUG 2010 Online Query Management System: An Innovative SAS/IntrNet Solution for Clinical Data Management Romain Miralles 12
SGF 2010 Aggregation without Aggravation: Determining Spatial Contiguity and Joining Geographic Areas Using Hashing Gwen Babcock source 17
SGF 2010 SAS Application Messaging: How to Integrate Disparate Processes in Your Service-Oriented Architecture Stephen A. Vincent source 13
NESUG 2009 Aggregation without Aggravation: Determining Spatial Contiguity and Joining Geographic Areas Using Hashing Gwen Babcock 17
NESUG 2009 Choosing the Right Technique to Merge Large Data Sets Efficiently Qingfeng Liang 9
WUSS 2009 CDISC for the Medical Device and Diagnostic Industry: An Update Carey G. Smoak source 3
WUSS 2009 How a SAS/IntrNet tool was created at the FDA for the detection of potential drug-induced liver injury using data with CDISC standard Kate Gelperin,
Ted J. Guo,
John Senior		 source 17
PharmaSUG 2009 Pharmacogenomics: JMP right in! Jason Baucom 5
SGF 2009 Choosing the Right Technique to Merge Large Data Sets Efficiently Qingfeng Liang source 9
PHUSE EU 2008 KEPT IN TRANSLATION: AVOIDING DATA LOSS AND OTHER PROBLEMS WHEN CONVERTING JAPANESE DATA Stephen Prust source 9
PNWSUG 2008 MODIFY The Most Under-Appreciated of the Data Step File Handling Statements Curtis E. Mack 12
NESUG 2008 Another Helping of HASH Lee Dodoo,
Stephen J. Rhoades		 18
PharmaSUG 2008 Labor-Saving SQL Constructs Brian P. Fairfield-Carter,
David W. Carr		 11
SGF 2008 Labor-Saving SQL Constructs Brian P. Fairfield-Carter,
David W. Carr		 source 10
NESUG 2007 Relationships Between CDISC Variables Linking Domains (relrec) (CDISC Variable Relationships Part 3 of 3) Susan Fehrer,
Russell M. Lavery		 12
WUSS 2007 Quick Record Lookup without an Index Paul A. Choate source 4
PHUSE EU 2007 Relationships between CDISC variables linking domains (relrec) Susan Fehrer,
Russell M. Lavery		 source 12
SGF 2007 Quick Record Lookup without an Index Paul A. Choate source 4
PNWSUG 2006 MODIFY The Most Under-Appreciated of the Data Step File Handling Statements Curtis E. Mack 12
SESUG 2006 Stars and Models: How to Build and Maintain Star Schemas Using SAS Data Integration Server in SAS9 Nancy A. Rausch source 24
NESUG 2006 Need a Speedy Index? RAM It! Lessia S. Shajenko,
Paul M. Dorfman		 14
SUGI 2006 Crafting Your Own Index: Why, When, How Paul M. Dorfman,
Lessia S. Shajenko		 source 14
SUGI 2006 Improve Database Transaction Processing Using MODIFY, the Most Under-Appreciated DATA Step File-Handling Statement Curtis E. Mack source 12
SUGI 2006 Stars and Models - How to Build and Maintain Star Schemas Using SAS ETL Server Nancy A. Rausch source 24
PNWSUG 2005 MODIFY The Most Under-Appreciated of the Data Step File Handling Statements Curtis E. Mack 12
SESUG 2005 _05 Managing a Many to Many Merge using Formats, Direct Access, and Implied Hashing source 8
SESUG 2005 The SQL Optimizer Project: _Method and _Tree in SAS 9.1 Russell M. Lavery source 57
NESUG 2005 Crafting Your Own Index: Why, When, How Paul M. Dorfman,
Lessia S. Shajenko		 10
SUGI 2005 The SQL Optimizer Project: _Method and _Tree in SAS 9.1 (broken file) Russell M. Lavery source 57
WUSS 2004 Matching without Unique Identifiers - Fuzzy Matching Applications with SAS Software Wade Bannister source 4
SUGI 2004 Mainframe SAS for the 21st Century Kryn Krautheim source 9
SESUG 2003 Data-driven Validation Rules: Custom Data Validation Without Custom Programming Don Hopkins source 8
SUGI 2003 The Horror of Bad Data Quality Henri Theuwissen,
Nancy Croonen		 source 7
SUGI 2002 Mining Web Server Logs: Tracking Users and Building Sessions Don Koch,
John C. Brocklebank,
Richard Roach		 source 4
NESUG 2001 Selecting Unrestricted and Simple Random With Replacement Samples Using Base SAS and PROC SURVEYSELECT David D. Chapman 9
WUSS 2001 Scalable Methods for the Quality Control of Patient Data Michael J. Yee source 6
NESUG 2000 Partially Transforming Hierarchical Data Sets for Sequential Processing Using Arrays Richard L. Downs Jr.,
Pura A. Perez		 8
NESUG 2000 SQL Summary Functions, Unions, and Aliases to Define a Risk Cohort and Risk Variables from a Record-based Study Janet Wikoff,
Lori Maiwald		 9
WUSS 1999 Summarizing Data Using PROC REPORT Theresa Famolaro source 5
SUGI 1999 Obtaining Response-Time and Service Level Information About Your SAS System Applications Terry Lewis,
Daniel J. Squillace		 source 10
SUGI 1999 Web Enabled Graphics with a SAS Data Warehouse Diane E. Brown source 6
MWSUG 1998 Web Enabled Graphics with a SAS Data Warehouse Diane E. Brown 6
NESUG 1998 Efficient Access to Data Warehouse With PROC SQL Pass Through Facility James Yang 7
PharmaSUG 1998 The Causes, Impact and Detection of Duplicate Observations Alice M. Cheng 11
PNWSUG 1997 Using SAS Software in Pharmacoepidemiological Research: Identifying Epidsodes of Drug Use and Determining Average Daily Dose Charlotte Corelle,
Majorie Bennett,
Richard E. Johnson,
Bentson McFarland		 3
MWSUG 1995 SQL Joins - The Long and The Short of It Paul Kent 10
NESUG 1995 A Creative Way to Read Stored Printed Reports Using the INPUT Statement and PROC TRANSPOSE Karen E. Davis 2
NESUG 1995 An Efficient Way to Condense Unbalanced Panel Data Andrew J. Epstein 2
SUGI 1995 SOL Joins - The Long and the Short of it Paul Kent source 10
SESUG 1994 rurORIALS Paul Kent 10
SUGI 1994 The SAS User Group Newsletter - Start the Presses! Andrew T. Kuligowski source 7
WUSS 1993 The Urge to Merge: A Computational Method for Linking Datasets With No Unique Identifier Robert M. Bell,
Joan Keesey,
Toni Richards		 source 6
SUGI 1993 Death Matching - An Algorithm and Comparison of Its Implementation in PROC SQL versus PROC SQL plus a DATA Step Charlotte Corelle,
Dean MacLaughlin,
Lois Drew,
Mary Longacre		 source 3
SUGI 1993 Getting to Know You, Getting to Know All About You: Simple Techniques for Forming a Relationship with Your Data Arthur L. Carpenter source 6
SUGI 1993 The Urge to Merge: A Computational Method for Linking Datasets With No Unique Identifier Joan Kessey,
Robert M. Bell,
Toni Richards		 source 6
SUGI 1993 Using SAS Software in Pharmacoepidemiologic Research: Identifying Episodes of Drug Use and Determining Average Daily Dose Charlotte Corelle,
Marjorie Bennett,
Bentson McFarland,
Richard E. Johnson		 source 3
SUGI 1992 A Binary Search for Non-Unique Keys Derek Drummond source 5
SUGI 1991 Using SAS/CONNECT and SAS/ACCESS Software to Access Data in a Distributed Environment Stephanie Creech,
Jana Van Wyk		 source 8
SUGI 1990 Adult Education Student Tracking System Margaret K. Schrempf source 2
SUGI 1990 CARDS: An Inverted List Database Created Using SAS Software Luke L. Diamond source 6
SUGI 1985 Conference Program Management Using SAS/FSPSoftware H. Pat Artis source 6
SUGI 1979 Correcting and Updating EBCDIC Files with SAS76 Marilyn Bodow source 5

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