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410 papers and 3 presentations; 337 titles.

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Conference × Year × Title × Authors Extras Pages
WUSS 2026 From Raw to Compliant: Applying Domain-Specific SAS Macros for Data Cut-Off in Clinical Trials Ballari Sen source 26
WUSS 2026 PROC SORT (then and) NOW Derek P. Morgan source 11
WUSS 2026 Simplifying SAS Viya: Explaining the Compute and CAS Servers, Caslibs, and In-Memory Data Carleigh Jo Crabtree source 18
PharmaSUG 2026 A fully automated PDF solution using SAS without third-party PDF tools Zhongan Chen source 10
PharmaSUG 2026 Trusting Your R Packages: A Practical, Risk-Based Approach to External Package Validation Radhika Etikala,
Valeria Duran		 source 14
PHUSE US 2026 A Proc Compare Enhancement Macro Chris Weiner source
presentation source		 12
PHUSE APAC 2026 SAS EG Tips and Tricks from a Statistical Programmer's Perspective Nipun S source
presentation source		 7
PHUSE EU 2025 Multiple Imputations Overview of Missing Data Problem, Solution Methods and SAS Implementation Dmytro Kalinin source
presentation source		 13
PHUSE EU 2025 Untangling the Dependencies Web Rhys McCrosson source
presentation source		 12
PharmaSUG 2025 Streamlining BIMO and Patient Profile Generation: A Python-Based Semi-Automated Approach Integrated with CSR Development Dmytro Skorba,
Mykyta Vysotskyi		 source 15
MWSUG 2024 Calculating Cardinality Ratio in Two Steps Ronald J. Fehd source 22
MWSUG 2024 List Processing using SQL Select Into to Replace Call Symputx Creating Indexed Arrays of Macro Variables Ronald J. Fehd source 13
PHUSE EU 2024 An Experiment on the Use of Altair SLC for Clinical Study Analytics Mark Holland,
Michael Byrne		 source
presentation source		 9
PHUSE EU 2024 Analysing Your SAS Log with User-Defined Rules Using an App or Macro Philip A. Mason source
presentation source		 11
PHUSE EU 2024 Blink and You Will Miss It! Daniel Lindenbaum source
presentation source		 9
SESUG 2024 Comparative Tools in SAS: Analyzing Self-Reported versus Imputed Values Neesha Nathwani,
Sarah Woodruff		 source 30
SESUG 2024 Examining the R datastep() Function David J. Bosak source 12
SESUG 2024 This Works on So Many Levels: Building Summary Tables in SAS with Hash Programming David V. Cole source 15
WUSS 2024 How RANK are your deciles? Using PROC RANK and PROC MEANS to create deciles based on observations and numeric values Lisa A. Mendez source 9
WUSS 2024 Integration of an R Language Function Within SAS to Perform Conditional Multivariate Saddlepoint Approximation Christopher Johnson source 8
WUSS 2024 PROC SORT (then and) NOW Derek P. Morgan source 11
PharmaSUG 2024 An Introduction to the SAS Transpose Procedure and its Options Timothy J. Harrington source 14
PharmaSUG 2024 Analyzing your SAS log with user defined rules using an app or macro. Philip A. Mason source 10
PharmaSUG 2024 Externally Yours - Adeptly Managing Data Outside Your EDC System Frank Canale source 38
PHUSE US 2024 Bridging the Gap Between the pharmaverse and Company Internal Resources Kangjie Zhang source
presentation source		 8
PHUSE US 2024 Effortless Table Generation: A SAS Macro for Streamlining Your Workflow Zhen (Laura) Li source
presentation source		 12
PHUSE US 2024 Eliminating Duplicative Maintenance of Statistical Programs In Parallel Analyses Using a Single Control File Kavitha Boinapally source
poster source		 4
PHUSE EU 2023 Metadata-Driven ADaM R-Code Generation by Leveraging Automation Potential Thiago Figueiredo,
Waldemar Miller		 source
presentation source		 31
WUSS 2023 Leveraging Logistic Regression and Bootstrap Sampling to Assess a Decision Threshold in Classification Predictive Analytics Colleen E. McGahan source 15
WUSS 2023 List Processing using SQL Select Into to Replace Call Symputx Creating Indexed Arrays of Macro Variables Ronald J. Fehd source 13
SESUG 2023 Getting Started with PROC DS2 James E. Blum,
Jonathan W. Duggins		 source 22
SESUG 2023 List Processing using SQL Select Into to Replace Call Symputx Creating Indexed Arrays of Macro Variables Ronald J. Fehd source 13
SESUG 2023 MISSING Mysteries for SAS Beginners Jinson J. Erinjeri source 9
PharmaSUG 2023 A Macro to Identify Repeating SAS BY Variables in a MERGE Timothy J. Harrington source 9
PharmaSUG 2023 Repetitive Analyses in SAS - Use of Macros Versus Data Inflation and BY Group Processing Bradford J. Danner,
Indrani Sarkar		 source 6
PharmaSUG 2023 Taming the Large SAS Dataset by Splitting it Up David W. Franklin source 5
SESUG 2022 Names From Template (NFT) Kannan Deivasigamani source 9
WUSS 2022 Calculating Cardinality Ratio in Two Steps Ronald J. Fehd source 23
WUSS 2022 PROC SORT (then and) NOW Derek P. Morgan source 11
PharmaSUG 2022 Automation of Variable Name and Label Mapping from Raw Data to Analysis Data Standards Xingshu Zhu,
Bo Zheng,
Li Ma		 source 9
PharmaSUG 2022 Fast hashes for complex joins Bartosz Szymecki source 12
PharmaSUG 2022 How RANK are your deciles? Using PROC RANK and PROC MEANS to create deciles based on observations and numeric values Lisa A. Mendez source 10
PharmaSUG 2022 Simple and Efficient Bootstrap Validation of Predictive Models Using SAS/STAT Software Matthew T. Slaughter,
Isaiah Lankham		 source 22
PHUSE EU 2021 Beyond P21 Data Checks [presentation] Abdulkadir Lokhandvala source
video		 24
PHUSE EU 2021 SAS Coding Efficiency: Developing a Performance Mindset [presentation] Richard Paterson source
video		 21
SESUG 2021 Missing Value Imputation Ross Bettinger source 34
PHUSE US 2021 Why Business Users Should Care About Systems Architecture [presentation] Hans-Peter Schreiter source
video		 16
PharmaSUG 2021 Imputation for Missing Dosing Time in NONMEM PopPK Datasets Shuqi Zhao source 8
PharmaSUG 2021 Overcoming the Challenge of SAS Numeric Date Comparisons Shikha Sreshtha source 7
PharmaSUG 2021 Programming Time Varying Concomitant Medication Covariates in NONMEM PopPK Dataset Dan Xiao,
Jing Su,
Shuqi Zhao,
Xiang Liu		 source 11
PharmaSUG 2021 Using PROC FCMP to Create Custom Functions in SAS Keith Shusterman,
Mario Widel		 source 12
SGF 2021 A SAS Macro to Perform Kaplan-Meier Multiple Imputation for Survival Analyses with Competing Events Jialin Han,
Sai Liu,
Margaret R. Stedman,
Maria E. Montez-Rath		 source 8
PHUSE EU 2020 Breaking Boundaries: Working Across Different Workspaces in LSAF Kai Wanke source
video
presentation source		 8
PHUSE EU 2020 PROC FCMP or Function You Create, Master and Proceed Iryna Boiko source
video		 4
SGF 2020 Let's See Further than One Observation: Applying Hash Objects for Typical Clinical Programming Tasks Valeriia Oreshko source 10
SGF 2020 Making Life Easier on the SAS End: Best Practices for Julie Plano,
Keli Sorrentino		 source 20
SGF 2020 PARSING: Using SAS When the Data Are Hiding in a Non-Standard Format Andrew T. Kuligowski source 12
PharmaSUG 2020 Implementing a LEAD Function for Observations in a SAS DATA Step Timothy J. Harrington source 12
PharmaSUG 2020 One Macro to create more flexible Macro Arrays and simplify coding Siqi Huang source 6
PharmaSUG 2020 Sometimes SQL Really Is Better: A Beginner's Guide to SQL Coding for DATA Step Users Brett Jepson source 16
PharmaSUG 2020 Transpose Procedure: Turning it Around Again Janet E. Stuelpner source 8
PHUSE US 2020 How to Build Compliance Mindset into A Team Habit Xiaohui Wang source
presentation source		 4
PHUSE EU 2019 Big SAS Code Navigation and Management Fred Ross,
Jessica Whittaker-Dixon		 source
presentation source		 8
PHUSE EU 2019 Innovative SQLs Joseph Murphy source
presentation source		 8
PHUSE EU 2019 Let's See Further than One Observation: Applying Hash Objects for Typical Clinical Programming Tasks Valeriia Oreshko source
presentation source		 8
PHUSE EU 2019 SDTM Validation Tool Anamaria Calai source
presentation source		 12
SESUG 2019 Analyzing Hospital Medicare Cost Report Data Using SAS - Updated with Output Kimberly Andrews source 19
SESUG 2019 Macros for Neural Network Modeling Ross Bettinger source 23
WUSS 2019 Automating ADSL Programming Using Pinnacle 21 Specifications Tracy Sherman,
Aakar Shah		 source 12
WUSS 2019 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman source 16
WUSS 2019 People Keep ASCIIng Me About These Characters Dan Konkler,
Rebecca Bowermaster,
Stephanie Ann Sanchez		 source 20
PharmaSUG 2019 Freq Out - Proc Freq's Quick Answers to Common Questions Christine McNichol source 8
PharmaSUG 2019 Making the Days Count: Counting Distinct Days in Overlapping or Disjoint Date Intervals Noory Y. Kim source 12
PharmaSUG 2019 Sum Fun with Flags! Sum Any Flagged Occurrence Data with FLAGSUM and Report It with FLAGRPT or PROC REPORT. Brendan Bartley source 31
SGF 2019 Dynamic Call Center Simulation in SAS: Revamping the Business Resiliency Process at JPMorgan Chase Jay P. Carini,
Amy Pielow,
Joel C. Weaver		 source 16
SGF 2019 Execution of User-Written DS2 Programs inside Apache Spark Using SAS In-Database Code Accelerator David Ghazaleh source 18
SGF 2019 Sometimes SQL Really Is Better: A Beginner's Guide to SQL Coding for DATA Step Users Brett Jepson source 17
SGF 2019 The Mother Of All Metadata Files: Using SAS Macros To Manage Metadata Hugh G. McCabe source 14
SCSUG 2018 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman source 16
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 Please Put Your Data in an Upright Position - Or How to Tackle Verticalisation Kristina Zweier source
presentation source		 9
SESUG 2018 Analyzing Hospital Medicare Cost Report Data Using SAS Kimberly Andrews source 19
SESUG 2018 CONSORT Diagrams in SGPLOT: Adding Efficiencies Shane Rosanbalm source 7
SESUG 2018 HASH Beyond Lookups - Take Another Look Elizabeth Axelrod source 11
SESUG 2018 Tips and Tricks for Ensuring Accurate Routine Data Processing when Logs are Redirected to Text Files Davia N. Moyse source 7
SESUG 2018 You're Doing It Wrong! Volume 001 Shane Rosanbalm source 4
MWSUG 2018 Leveraging SHEWHART Procedure Options to Monitor and Evaluate Improvements in Healthcare Roderick Jones,
Lynn (Xiaohong) Liu		 12
MWSUG 2018 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman 16
MWSUG 2018 Seeing the Forest for the Trees: Part Deux of Defensive Coding by Example Donna E. Levy,
Nancy Brucken		 10
PharmaSUG 2018 Automation of STDM dataset integration and ADaM dataset formation Rinki Jajoo,
William Wei		 source 11
PharmaSUG 2018 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman source 16
PharmaSUG 2018 Seeing the Forest for the Trees: Part Deux of Defensive Coding by Example Donna E. Levy,
Nancy Brucken		 source 10
SGF 2018 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman source 16
SGF 2018 Mitigating the Effects of Class Imbalance Using SMOTE and Tomek Link Undersampling in SAS Kyle Biron source 20
SGF 2018 Run-Time Validation of SAS Jobs: A Threesome of Error-Throwing Macros Quentin McMullen source 18
SGF 2018 Seeing the Forest for the Trees: Part Deux of Defensive Coding by Example Nancy Brucken,
Donna E. Levy		 source 10
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 Data Cleaning Technique for Business Analytics: What Stats Van Do for DM Adam Korczynski source
presentation source		 16
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 Effectively Utilizing Loops and Arrays in the DATA Step Arthur X. Li source 17
WUSS 2017 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman source 14
PharmaSUG 2017 Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets Joshua M. Horstman source 10
SGF 2017 Improving Efficiency in SAS Enterprise Guide: Parallel Processing and Other Hidden Gems Steven J. First,
Benjamin First		 source 21
SGF 2017 More than a Report: Mapping the TABULATE Procedure as a Nested Data Object Jason Phillips source 8
SCSUG 2016 Anatomy of a Merge Gone Wrong Joshua M. Horstman source 5
SCSUG 2016 Using INFILE and INPUT Statements to Introduce External Data into the SAS System Andrew T. Kuligowski source 18
SESUG 2016 Are You Sure That Is Correct?: An Overview Of Good Practices For Dataset And Output Validation Gregory Weller source 8
SESUG 2016 The HPSUMMARY Procedure: A Younger (and Brawnier) Cousin to an Old SAS Friend Anh P. Kellermann,
Jeffrey D. Kromrey		 source 9
PHUSE EU 2016 Fast and High-quality Validation Process Andrea Parodi,
Dimitri Petratchenko		 source
presentation source		 7
PHUSE EU 2016 How to Handle Different Versions of SDTM & Define Generation in a Single Day Edwin Ponraj Thangarajan,
Giri Balasubramanian		 source
presentation source		 22
PHUSE EU 2016 SAS, Java & Excel: A Ménage á Trois Dana Vinzelberg source
presentation source		 8
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 Anatomy of a Merge Gone Wrong Joshua M. Horstman 5
MWSUG 2016 Calculating Cardinality Ratio in Two Steps Ronald J. Fehd 22
MWSUG 2016 How to Speed Up Your Validation Process Without Really Trying Alice M. Cheng,
Mike Wise		 22
WUSS 2016 How to Speed Up Your Validation Process Without Really Trying Alice M. Cheng,
Mike Wise,
Justina M. Flavin		 source 20
WUSS 2016 Making Prompts Work for You: Using SAS Enterprise Guide Prompts with Categorization of Output Edward Lan,
Kai-Jen Cheng		 source 5
WUSS 2016 What just happened? A visual tool for highlighting differences between two data sets. Steve Cavill source 18
PharmaSUG 2016 Best Practices: Subset Without Getting Upset Mary F. O. Rosenbloom,
Kirk Paul Lafler		 source 17
PharmaSUG 2016 Generalized Problem-Solving Techniques for De-bugging and Diagnosing Logic Errors Brian P. Fairfield-Carter,
Tracy Sherman		 source 12
PharmaSUG 2016 Using GTL Generating Customized Kaplan-Meier Survival Plots Joanne C. Zhou source 12
SGF 2016 How to Speed Up Your Validation Process Without Really Trying Alice M. Cheng,
Justina M. Flavin,
Michael Wise		 source 20
SGF 2016 The HPSUMMARY Procedure: An Old Friend's Younger (and Brawnier) Cousin Anh P. Kellermann,
Jeffrey D. Kromrey		 source
presentation		 9
MWSUG 2015 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski 10
MWSUG 2015 Slice and Dice your customers easily by using SAS Clustering Procedures Yanping Shen 9
PHUSE EU 2015 Clinical data to information, quick, standardised and validated with knowledge of proc FCMP Cathal Gallagher source
presentation source		 7
WUSS 2015 3N Validation to Validate PROC COMPARE Output Amarnath Vijayarangan source 6
WUSS 2015 How to Speed Up Your Validation Process Without Really Trying Alice M. Cheng source 23
WUSS 2015 ODS Output Data Sets That Work for You Stuart D. Long,
Edward Heaton,
Daniel R. Scharf		 source 29
WUSS 2015 S-M-U (Set, Merge, and Update) Revisited Andrew T. Kuligowski source 13
PharmaSUG CN 2015 Application of Output Delivery System in Creating Customized Targets Yuan Wang 6
PharmaSUG CN 2015 Effectively Utilizing Loops and Arrays in the DATA Step Arthur X. Li 17
PharmaSUG 2015 Automated Checking Of Multiple Files Kathyayini Tappeta source 7
PharmaSUG 2015 PROC TRANSPOSE For Fun And Profit John J. Cohen source 18
PharmaSUG 2015 Unpacking an Excel Cell: Dealing with Multi-Line Excel Cells in SAS Lucheng Shao source 10
PharmaSUG 2015 Using INFILE and INPUT Statements to Introduce External Data into SAS Andrew T. Kuligowski source 18
PharmaSUG 2015 Using Meta-data to Identify Unused Variables on Input Data Sets Keith Hibbetts source 4
SGF 2015 Analyzing Parking Meter Transactions Using SAS Procedures Anders Milhøj source 12
SGF 2015 Anatomy of a Merge Gone Wrong Joshua M. Horstman source 5
SGF 2015 Best Practices: Subset Without Getting Upset Mary F. O. Rosenbloom,
Kirk Paul Lafler		 source 17
SGF 2015 S-M-U (Set, Merge, and Update) Revisited Andrew T. Kuligowski source 13
SESUG 2014 PROC TRANSPOSE For Fun And Profit John J. Cohen source 18
PHUSE EU 2014 Define your Own SAS Functions for Date and Numeric Validation using PROC FCMP Jason Smith source
presentation source		 5
PHUSE EU 2014 PROC EASTMONITOR - A SAS Add-on for Monitoring Adaptive Clinical Trials Sheetal Solanki,
Ajay Sathe		 source
presentation source		 15
PHUSE EU 2014 QC: Manual vs Program - A Personal View Helen Nicholson source
presentation source		 6
PHUSE EU 2014 Using SAS Arrays Ruurd Bennink source
presentation source		 7
MWSUG 2014 How Do I ...? Some Beginners FAQs Peter W. Eberhardt,
Audrey Yeo		 11
WUSS 2014 Advanced Multiprocessing Techniques for Performance Improvement of SAS Processes Viraj R Kumbhakarna source 17
WUSS 2014 Best Practices: Subset Without Getting Upset Mary F. O. Rosenbloom,
Kirk Paul Lafler		 source 17
WUSS 2014 How can I simplify ETL when I only have Base SAS Steve Cavill source 15
PharmaSUG 2014 %ME: A SAS Macro to Assess Measurement Equivalence for Patient-Reported Outcome Measures Qinlei Huang source 8
PharmaSUG 2014 A SAS Macro to address PK timing variables issues Timothy J. Harrington source 14
PharmaSUG 2014 Automate the Process of Image Recognizing a Scatter Plot: An Application of Non-parametric Cluster Analysis in Capturing Data from Graphical Output Zhaojie Wang source 11
PharmaSUG 2014 Standardization of Confidence Intervals in PFS Tables - a Macro Approach John Saida Shaik,
Boxun Zhang		 source 4
SGF 2014 Effectively Utilizing Loops and Arrays in the DATA Step Arthur X. Li source 17
SGF 2014 Modeling Loss Given Default in SAS/STAT Xiao Yao,
Jonathan Crook,
Galina Andreeva		 source 9
SGF 2014 Nonnegative Least Squares Regression in SAS Matthew Duchnowski source 5
SGF 2014 The SAS Hash Object: It's Time To .find() Your Way Around Peter W. Eberhardt source 17
WUSS 2013 Going the Distance: Google Maps Capabilities in a Friendly SAS Environment Anton Bekkerman source 9
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 One problem - Multiple solutions; various ways of removing duplicates from dataset using SAS Jaya Dhillon source 6
SCSUG 2013 The Concepts and Practice of Analysis with SAS Enterprise Guide Christopher W. Schacherer source 48
SESUG 2013 Parallel processing techniques for performance improvement for SAS processes: Part II Viraj R Kumbhakarna source 17
MWSUG 2013 Advanced Multithreading Techniques for Performance Improvement of SAS Processes Viraj R Kumbhakarna 17
MWSUG 2013 Anatomy of a Merge Gone Wrong James Lew,
Joshua M. Horstman		 5
MWSUG 2013 Effectively Utilizing Loops and Arrays in the DATA Step Arthur X. Li 17
MWSUG 2013 The Essence of DATA Step Programming Arthur X. Li 19
NESUG 2013 Continuous Enrollment Requirements in Epidemiologic Studies Jennifer R. Popovic 12
NESUG 2013 OUT= Is on the Way Out - Use ODS OUTPUT Instead Stanley E. Fogleman 4
NESUG 2013 PROC TRANSPOSE For Fun And Profit John J. Cohen 18
NESUG 2013 The Ultimate Macro to Generate Summary Tables Lan Hu,
Xiaoqiang Wang		 12
PharmaSUG 2013 Anatomy of a Merge Gone Wrong James Lew,
Joshua M. Horstman		 source 5
PharmaSUG 2013 Combining Analysis Results from Multiply Imputed Categorical Data Bohdana Ratitch,
Ilya Lipkovich,
Michael O'Kelly		 source 19
PharmaSUG 2013 Effectively Utilizing Loops and Arrays in the DATA Step Arthur X. Li source 17
PharmaSUG 2013 Implementation of Breast Cancer Risk Assessment Tool using SAS Yuqin Li,
Lihua Chen,
Xiaohai Wan,
Alan Chiang		 source 8
SGF 2013 OUT= Is on the Way Out - Use ODS OUTPUT Instead Stanley E. Fogleman source 4
SGF 2013 The Concepts and Practice of Analysis with SAS Enterprise Guide Christopher W. Schacherer source 48
SGF 2013 Using SAS to Assess Individuals? Best Performance in Multiple Dimensions Aude Pujula,
David Maradiaga		 source 5
SESUG 2012 Learning PROC SQL the DATA Step Way Meghal Parikh source 8
SESUG 2012 Multiple Imputation for Ordinal Variables: A Comparison of SUDAAN's PROC IMPUTE vs. PROC MI Multiple Imputation source 12
SESUG 2012 ODS Output Data Sets That Work for You Stuart D. Long,
Edward Heaton,
Daniel R. Scharf		 source 29
SESUG 2012 Proc Summary Options Beyond The Basics Susmita Pattnaik source 11
MWSUG 2012 Avoiding Pitfalls when Merging Data James Lew,
Joshua M. Horstman		 5
MWSUG 2012 Effectively Utilizing Loops and Arrays in the DATA Step Arthur X. Li 17
MWSUG 2012 The SAS Hash Object: It's Time To .find() Your Way Around Peter W. Eberhardt 17
MWSUG 2012 Using INFILE and INPUT Statements to Introduce External Data into SAS Andrew T. Kuligowski 18
WUSS 2012 I Hate Typing Variable Names Mark Kirkham source 4
WUSS 2012 The SAS Hash Object: It's Time To .find() Your Way Around Peter W. Eberhardt source 17
PharmaSUG CN 2012 The SAS Hash Object: It's Time To .find() Your Way Around Peter W. Eberhardt 17
PharmaSUG 2012 Efficiently Trim Character Variable Lengths to Fit Data, Reduce Dataset Size Wayne (Weizhen) Zhong source 7
PharmaSUG 2012 Metadata: Some Fundamental Truths Frank C. DiIorio source 10
PharmaSUG 2012 One Macro Call to a Table with both Frequency and Summary Elements from a Subject-Level Dataset Wayne (Weizhen) Zhong source 9
PharmaSUG 2012 Pattern-Mixture Models as Linear Combinations of Least Squares Means from MMRM with Delta Method Variance Estimation Bohdana Ratitch,
Michael O'Kelly		 source 15
PharmaSUG 2012 Short-circuiting PROC COMPARE: Techniques for Focusing Dataset Comparisons Tracy Sherman,
Brian P. Fairfield-Carter		 source 8
SGF 2012 Batch Production of Driving Distances and Times Using SAS and Web Map APIs Ash Roy,
Yingbo Na		 source 7
SGF 2012 Take a Fresh Look at SAS Enterprise Guide: From point-and-click ad hocs to robust enterprise solutions Christopher W. Schacherer source 26
SGF 2012 The SAS Hash Object: It's Time To .find() Your Way Around Peter W. Eberhardt source 17
SCSUG 2011 A Well Designed Process and QC Tool for Integrated Summary of Safety Reports Huei-Ling Chen source 6
SCSUG 2011 Take a Fresh Look at SAS Enterprise Guide: From point-and-click ad hocs to robust enterprise solutions Christopher W. Schacherer source 26
SCSUG 2011 Using Proc Logistic, SAS Macros and ODS Output to evaluate the consistency of independent variables during the development of logistic regression models. An example from the retail banking industry Alexandros Vidras source 9
SESUG 2011 Proc MIXED - Right Options to get Right Output Shilpa C. Edupganti,
Sheetal Nisal		 source 9
PHUSE EU 2011 Ensuring Compliant and Consistent Data Mappings for SDTM-based Studies - an ICON Approach Jennie McGuirk,
Steven Thacker		 source
presentation source		 16
MWSUG 2011 Dealing with Duplicates in Your Data Joshua M. Horstman,
Roger D. Muller		 7
MWSUG 2011 Take a Fresh Look at SAS Enterprise Guide: From point-and-click ad hocs to robust enterprise solutions Christopher W. Schacherer 26
MWSUG 2011 Using SAS to Create Sales Expectations for Everyday and Seasonal Products Lory Ellebracht,
Jamie Netherton,
Casey Gentry		 10
NESUG 2011 Metadata: Some Fundamental Truths Frank C. DiIorio 9
NESUG 2011 Proc Mixed - Right Options to Get the Right Output Shilpa C. Edupganti,
Sheetal Nisal		 10
PharmaSUG 2011 Implementation of Pattern-Mixture Models Using Standard SAS/STAT Procedures Bohdana Ratitch,
Michael O'Kelly		 source 10
PharmaSUG 2011 Leave Your Bad Code Behind: 50 Ways to Make Your SAS Code Execute More Efficiently William E. Benjamin Jr. source 20
PharmaSUG 2011 The Many Ways to Effectively Utilize Array Processing Arthur X. Li source 14
SGF 2011 ODS Output Data Sets That Work for You Stuart D. Long,
Edward Heaton,
Daniel R. Scharf		 source 29
SGF 2011 SAS Enterprise Guide Options: Let the Tools Work for You Harsha M. Kotian,
Susan M. Jumper		 source 20
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
SGF 2011 The SAS Hash Object: It's Time To .find() Your Way Around Peter W. Eberhardt source 17
NESUG 2010 %whatChanged: A Tool for the Well-Behaved Macro Frank C. DiIorio 14
NESUG 2010 PROC SQL: Tips and Translations Gail Jorgensen,
Susan P. Marcella		 23
NESUG 2010 TRACKING DATASET DEPENDENCIES IN CLINICAL TRIALS REPORTING Binoy Varghese,
Satyanarayana Mogallapu		 10
NESUG 2010 Windows Application Using .NET and SAS to Produce Custom Rater Reliability Reports Sailesh Vezzu 14
WUSS 2010 Get a Grip on Arrays in Just 50 Minutes! Arthur X. Li source 14
WUSS 2010 The Building Blocks of SAS Datasets - S-M-U (Set, Merge, and Update) Andrew T. Kuligowski source 13
PHUSE EU 2010 A Case Study in Using Unit Testing as a Method of Primary Validation Ross Farrugia source
presentation source		 12
MWSUG 2010 Set, Match, Merge ... Don't You Love SAS Peter W. Eberhardt,
Ying Liu		 19
MWSUG 2010 The SAS Hash Object: It's Time To .find() Your Way Around - Hands-On Workshop Peter W. Eberhardt 17
SESUG 2010 %whatChanged: A Tool for the Well-Behaved Macro Frank C. DiIorio source 14
SESUG 2010 Leave Your Bad Code Behind: 50 Ways to Make Your SAS Code Execute More Efficiently William E. Benjamin Jr. source 20
SESUG 2010 Set, Match, Merge ... Don't You Love SAS Peter W. Eberhardt,
Ying Liu		 source 19
PharmaSUG 2010 %TABLEMAKER: Data Reporting Made Easy Bernadette H. Johnson 6
PharmaSUG 2010 %whatChanged: A Tool for the Well-Behaved Macro Frank C. DiIorio 14
PharmaSUG 2010 PROC REPORT - Compute Block and Conditional Footnote Yumi Sembongi 20
PharmaSUG 2010 RTF_READ: Decoding RTF Files Sandeep Juneja 6
PharmaSUG 2010 The SAS Hash Object: It's Time To .find() Your Way Around - Hands-On Workshop Peter W. Eberhardt 17
PharmaSUG 2010 The SAS Hash Object: It's Time To .find() Your Way Around - Tutorial Peter W. Eberhardt 17
SGF 2010 A Grad Student 'How-To' Paper on Grant Preparation: Preliminary Data, Power Analysis, and Presentation Elisa L. Priest,
Derek Blankenship		 source 14
SGF 2010 Faster Results by Multi-threading DATA Steps Ian J. Ghent source 7
SGF 2010 Get the Scoop on the Loop: How Best to Write a Loop in the DATA Step Arthur X. Li source 19
SGF 2010 The SAS Hash Object: It's Time To .find() Your Way Around Peter W. Eberhardt source 17
SGF 2010 Using PROC CONTENTS Output to Perform Quality Control Checks on SDTM Data Sets Jennifer M. Srivastava source 6
SESUG 2009 PROC MIXED: Macro to assess fixed and random effects for significance using the Likelihood Ratio test and the approximate Mixture Method Barbara H. Bardenheier source 7
PHUSE EU 2009 Macro to manage the PCSA Claude Guyot source
presentation source		 3
PHUSE EU 2009 Safety analysis using Bayesian simulation methods in SAS 9.2 Armin Gemperli source 8
PHUSE EU 2009 The Perfect Match - an appreciation of the functionality of the dataset MERGE Diana Stuart source 5
MWSUG 2009 Effective Use of RETAIN Statement in SAS Programming Yi Zhao 4
NESUG 2009 Customizing a Correlation Matrix That Would Make Pearson Proud Aaron Hill 10
NESUG 2009 PROC SQL Tips and Techniques Gail Jorgensen,
Susan P. Marcella		 23
NESUG 2009 The Building Blocks of SAS Datasets - S-M-U (Set, Merge, and Update) Andrew T. Kuligowski 13
WUSS 2009 Leave Your Bad Code Behind: 50 Ways to Make Your SAS Code Execute More Efficiently William E. Benjamin Jr. source 20
WUSS 2009 Solving Your Problems with SAS Enterprise Guide: SAS without Programming AnnMaria De Mars source 18
WUSS 2009 The Fundamentals of Data Step Programming I: The Essence of Data Step Programming and By-Group Processing Arthur X. Li source 20
WUSS 2009 The Fundamentals of DATA Step Programming II: Looping Arthur X. Li source 13
PharmaSUG 2009 A Macro for Transforming Almost Any Character Calendar Date into a SAS Date Value Ruben Chiflikyan,
Mila Chiflikyan,
Donna Medeiros		 12
PharmaSUG 2009 Chic FREQ and UNIVARIATE Jasmin Fredette 14
PharmaSUG 2009 Concepts and Ideas for Developing and Maintaining a Utility Toolbox of SAS Statistical Procedures David W. Carr 6
PharmaSUG 2009 Sweet Smell of SucSAS - When Your DATA Step Does What is Intended!! Arthur X. Li 19
WUSS 2008 The Essence of DATA Step Programming Arthur X. Li source 19
SESUG 2008 NOTEs in a SASLOG : Of LOST CARDs and MERGE Statements with Repeats of By Values Andrew T. Kuligowski source 14
PHUSE EU 2008 A Collection of SAS Macros to Calculate Odds Ratios using Spline Regression Martin Gregory source 9
PHUSE EU 2008 Automating Elements of Validation in the Context of an ISE/ISS Paul Kearney source 10
PHUSE EU 2008 Concepts and Ideas for Developing and Maintaining a Utility Toolbox of SAS Statistical Procedures David W. Carr source 6
MWSUG 2008 Using Direct Standardization SAS Macro for a Valid Comparison in Observational Studies Daojun Mo,
Xia Li,
Alan Zimmermann		 11
PNWSUG 2008 MODIFY The Most Under-Appreciated of the Data Step File Handling Statements Curtis E. Mack 12
NESUG 2008 HELP! - My MERGE Statement Has More Than One Data Set With Repeats of BY Values! Andrew T. Kuligowski 5
NESUG 2008 How Do I Love Hash Tables? Let Me Count The Ways! Judy Loren 14
PharmaSUG 2008 Automated SAS Macro for Adverse Event Logistic Regression Analysis Suhas R. Sanjee 8
PharmaSUG 2008 EZTABLE Macros Daniel Huang 12
SGF 2008 How Do I Love Hash Tables? Let Me Count The Ways! Judy Loren source 14
SGF 2008 Range Formats Made Easy A CreateRangeFormat Custom Task for SAS Enterprise Guide Petr Hustak source 9
NESUG 2007 Does Your Application Have a Performance Problem? Put It in a SAS Pipe and Smoke It! (An Introduction to SAS Pipes) Robert L. Russell 11
NESUG 2007 Geocoding and PROC GMAP - Tools for Presenting Spatial Data Michael G. Eberhart 17
NESUG 2007 Using SAS ODS to Extract and Merge Statistics from Multiple SAS Procedures into a Single Summary Report, a Detailed Methodology Stuart D. Long,
Jeffrey M. Abolafia,
Lawrence Park		 22
SESUG 2007 Set, Match, Merge ... Don't You Love SAS Peter W. Eberhardt,
Ying Liu		 source 19
SESUG 2007 Using INFILE and INPUT Statements to Introduce External Data into the SAS System Andrew T. Kuligowski source 18
WUSS 2007 The TRANSPOSE Procedure or How to Turn your Data Around David Fickbohm source 10
PHUSE EU 2007 A SAS Macro for breaking pages Michael Knoessl source 4
SCSUG 2007 How Do I Love Hash Tables? Let Me Count The Ways! Judy Loren 14
SCSUG 2007 Using INFILE and INPUT Statements to Introduce External Data into the SAS System Andrew T. Kuligowski 18
PNWSUG 2007 Using INFILE and INPUT Statements to Introduce External Data into the SAS System Andrew T. Kuligowski 18
PharmaSUG 2007 Automatic Creation of Analysis Datasets for Clinical Trials - A Macro Program John H. Adams 17
PharmaSUG 2007 Combining ODS Output Datasets to Increase Program Clarity and Reduce Macro Load Rod Norman 7
PharmaSUG 2007 Proc Format Advanced Techniques: Multi-label and Nested Formats Tatiana Nevmyrych,
Jennifer Clark		 4
PharmaSUG 2007 The TRANPOSE Procedure or How to Turn It Around Janet E. Stuelpner 9
SGF 2007 A Generic Method of Parallel Processing in Base SAS 8 and 9 Sassoon Kosian source 8
SGF 2007 SAS Data Integration Studio and SAS Macro - Working in Harmony for Data Warehousing Projects Tatyana Kovtun source 10
PNWSUG 2006 MODIFY The Most Under-Appreciated of the Data Step File Handling Statements Curtis E. Mack 12
MWSUG 2006 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski 10
SCSUG 2006 Flattening Dependent Tables from Relational Databases for Use in SAS Processing David Welch 34
SCSUG 2006 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski 10
PHUSE EU 2006 Save Time: Program Your Output Specs Hansjörg Frenzel,
James Witt		 source 11
PHUSE EU 2006 Sorting by formatted values Jim Groeneveld source 4
PHUSE EU 2006 The Output Bundle: A Solution for a Fully Documented Program Run Carl Herremans source 6
SESUG 2006 Designing an Application with Business Intelligence Brian Deitch source 19
SESUG 2006 ET06 DATALINES, Sequential Files, CSV, HTML and More - Using INFILE and INPUT Statements to Introduce External Data into the SAS System Andrew T. Kuligowski source 18
SESUG 2006 Using SAS ODS to Extract and Merge Statistics from Multiple SAS Procedures into a Single Summary Report, a Detailed Methodology Stuart D. Long source 21
NESUG 2006 Designing an Application with Business Intelligence Brian Deitch 19
NESUG 2006 How Do I Love Hash Tables? Let Me Count The Ways! Judy Loren 14
NESUG 2006 It's About Time! A Primer on Time-Slotting of Data Using SAS Maria Y. Reiss 13
NESUG 2006 MIMO: Multiple Inputs Multiple Outputs - Multiplying the Fun while doing the Data Step John Fahey 9
PharmaSUG 2006 Large Scale Standard Macros - A Methodical Approach to Development and Implementation Jeremy Gratt,
John H. Adams		 18
PharmaSUG 2006 Mapping Clinical Data to a Standard Structure: A Table Driven Approach Nancy Brucken,
Paul K. Slagle		 7
PharmaSUG 2006 PROC FORMAT is Our Friend Erin M. Christen 20
SUGI 2006 AMMI Macros for Multiplicative Interaction Models Eun-Joo Lee,
Dallas E. Johnson		 source 10
SUGI 2006 DATALINES, Sequential Files, CSV, HTML, and More - Using INFILE and INPUT Statements to Introduce External Data into the SAS System Andrew T. Kuligowski source 18
SUGI 2006 FREQ n' MEANS Marge Scerbo,
Michael S. Lajiness		 source 19
SUGI 2006 Improve Database Transaction Processing Using MODIFY, the Most Under-Appreciated DATA Step File-Handling Statement Curtis E. Mack source 12
SUGI 2006 Project Duplication: Eradication Techniques Monal Kohli source 9
SUGI 2006 The TRANSPOSE Procedure or How to Turn It Around Janet E. Stuelpner source 9
SUGI 2006 Using SAS ODS to Extract and Merge Statistics from Multiple SAS Procedures Stuart D. Long,
Jeffrey M. Abolafia,
Lawrence Park		 source 21
PNWSUG 2005 MODIFY The Most Under-Appreciated of the Data Step File Handling Statements Curtis E. Mack 12
SESUG 2005 Proc Transpose or How to Turn It Around Janet E. Stuelpner source 7
SESUG 2005 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski source 10
PHUSE EU 2005 The Dataset Diet - How to transform short and fat into long and thin Kathryn Wright source 6
NESUG 2005 Freq n' Means Marge Scerbo,
Michael S. Lajiness		 19
NESUG 2005 Large Scale Standard Macros - A Methodical Approach to Development and Implementation Jeremy Gratt,
John H. Adams		 18
PharmaSUG 2005 %KMPlot - An Enhancement of SAS PROC LIFETEST Weifeng Xu,
William W.B. Wang		 8
PharmaSUG 2005 A Technique for Producing Sorted Columns with a Hanging First Line Using PROC REPORT David C. Izard,
David C. Chen		 6
PharmaSUG 2005 Preventing Data Loss when Combining SAS Datasets John Cantrell 9
PharmaSUG 2005 Utility Macros Used in the Process for Database Translations Yuguang Zhao,
Jingchun Yu		 3
SUGI 2005 Contrasting Programming Techniques for Summarizing Voluminous SAS Output Using the SAS Output Delivery System (ODS) Stuart D. Long source 17
SUGI 2005 PROC FREQ and PROC MEANS: To Stat or Not to Stat Marge Scerbo,
Michael S. Lajiness		 source 17
NESUG 2004 Contrasting programming techniques for summarizing voluminous SAS output using the SAS Output Delivery System (ODS) (PROC FREQ as an example) Stuart D. Long,
Lawrence Park		 10
SCSUG 2004 SAS/ACCESS to External Databases: Wisdom for the Warehouse User Judy Loren 10
SESUG 2004 Building Efficient State Transition Diagrams from Charges, Collection and Call Detail Transactional Feeds Brett C. Peppe source 19
SESUG 2004 How to Incorporate Old SAS Data into a New DATA Step, or "What is S-M-U?" Andrew T. Kuligowski source 13
WUSS 2004 Contrasting programming techniques for summarizing voluminous SAS output using the SAS Output Delivery System (ODS) (PROC FREQ as an example) Stuart D. Long,
Lawrence Park		 source 16
WUSS 2004 Creating Custom Tables Using SAS Tyler Cole source 11
MWSUG 2004 Contrasting Programming Techniques for Summarizing Voluminous SAS Output Using the SAS ODS Stuart D. Long,
Lawrence Park		 17
PNWSUG 2004 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski 11
PharmaSUG 2004 One Frequency Macro for All Frequency Tables Sam Mao 9
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 Introduction to ODS Lauren E. Haworth source 14
WUSS 2003 A Better Transpose: %TRANSPO Macro Preserves Variable Attributes Ted Clay source 3
WUSS 2003 Taming Your Metadata Part I: A Solution for Incorporating Data Documentation into the Programming Process Peter Godard source 6
SCSUG 2003 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski 11
SESUG 2003 Contrasting programming techniques for summarizing voluminous SAS output using the SAS Output Delivery System (ODS) (PROC FREQ as an example) Stuart D. Long,
Lawrence Park		 source 10
SESUG 2003 Developing a Marketing Geographic Segmentation System Using SAS Software Kellie M. Poulin,
Allison N. Freeman		 source 10
SESUG 2003 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski source 10
SESUG 2003 Tricks of A Truly Lazy SAS Programmer Christopher Toppe,
Independent Sector		 source 9
PharmaSUG 2003 SAS Macro to Create ADDL Records To Estimate Dosing Not Represented in the Collected Data, In a NONMEM Population Pharmacokinetic Analysis Dataset Richard Schneck,
Mike Heathman,
Lynn Reynolds		 6
PharmaSUG 2003 SQL for People Who Don't Think They Need SQL Erin M. Christen 8
SUGI 2003 P-Value Generation Simplified with a Single SAS Macro Christopher S. Hord,
Peter J. Anderson		 source 3
SUGI 2003 SAS/ACCESS to External Databases: Wisdom for the Warehouse User Judy Loren source 9
NESUG 2002 Don't Resort to Re-Sort Elizabeth Axelrod 2
SESUG 2002 The Lag-o-Matic: An Improved Method for Selecting the Lag Structure of Multiple Predictor Variables in the Absence of Theory David C. Sharp,
Stephen M. Finnigan		 source 5
PharmaSUG 2002 %Addval: A SAS Macro Which Completes the Cartesian Product of Dataset Observations for All Values of a Selected Set of Variables Rich Schiefelbein 6
PharmaSUG 2002 Fast Two-Sample Permutation Tests, Even When One Sample is Large, that Efficiently Maximize Power Under Crude Monte Carlo Sampling John D. Opdyke 10
PharmaSUG 2002 Macros for Model Building, Summarizing, and Displaying Results of Stepwise Logistic Regressions Lori S. Parsons 6
SUGI 2002 Macros for Model Building, Summarizing, and Displaying Results of Stepwise Logistic Regressions Lori S. Parsons source 6
WUSS 2001 CONCAT.SAS: A Macro for Concatenation of Grouped Multi-Record Narrative Text Roy Henrichs source 4
WUSS 2001 Making EXCEL Graphs from PROC LIFETEST Output William N. Anderson source 3
SUGI 2001 When PROC ACCESS Says NO to Excel 97/2000, DDE Says YES Still Eric T. Sun,
Eric Kammer		 source 5
WUSS 2000 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski source 5
WUSS 2000 Summarizing to the One-Record-Pere-Oerson Using PROC SUMMARY: When to Use CLASS and When to Use BY Jenny Yu source 6
SUGI 2000 LabOne's Production Reporting Environment - Post-Web Steven D. Beakley source 2
SUGI 2000 Multiple Imputation for Missing Data: Concepts and New Development Yang Yuan source 10
SUGI 2000 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski source 5
SESUG 1999 Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs Andrew T. Kuligowski source 8
WUSS 1999 Site Specific Reports: Comparing each part to the whole using numbers and figures Jenny Yu source 6
NESUG 1999 A Method for Developing Data-Driven Market Area Clusters Joseph S. Brenner 9
SUGI 1999 Poisson Regression Adjustment of Event Rates and Its Macro Procedure ADJ_POIS Dingyi Zhao source 6
WUSS 1998 The Elements of SAS Programming Style Frank C. DiIorio source 5
WUSS 1998 The Problem with NODUPLICATES, Continued Jack Hamilton source 5
SESUG 1998 Programmatic Generation of Table Specifications Using the SAS Macro Facility Weimin "WilHam" Sun,
Caroline Stewart		 10
PNWSUG 1998 Stepwise Anything: Reading in Regression Procedure Output for Further Testing Ted Clay,
Linda Remy		 10
SUGI 1998 A Macro to Generate All Combinations of n Items Taken k at a Time (How It Was Designed and Written, and How It Might Be Adapted to Other Uses: A Programming Example) Francis J. Kelley source 9
NESUG 1997 Drill Down Till You Drop: OLAP Without Windows Ralph Winters 10
NESUG 1997 Gentle Introduction to Information Theoretic Model Selection Criteria and Their Application in Clinical Trials Xi Chen 4
SEUGI 1997 The correction of wrong results obtained with the "Agree"option in PROC FREQ for contingency tables with empty rows and columns Richard Vonk,
Werner Wierich		 source 8
SESUG 1996 Software Validation and Testing Andrew T. Kuligowski 9
SUGI 1996 Data about Data: An Introduction to Dictionary Tables Frank C. Dilorio,
Nancy J. Michal		 source
SUGI 1996 SAS Software Tips: My Experience as a SAS-L MVP Philip A. Mason source 7
SUGI 1996 Software Validation and Testing Andrew T. Kuligowski source 9
MWSUG 1995 Simulation and Bootstrapping in the SAS System: A tutorial using PROC IML Paul A. Thompson 10
SESUG 1995 Advanced Tutorials Data About Data: An Introduction to Dictionary Tables Frank C. Dilorio 7
SESUG 1995 Extended Uses of the CONTENTS Procedure Steven A. Wright 5
SESUG 1995 The Elements of SAS Programming Style Frank C. Dilorio,
Jean Cocteau		 6
SEUGI 1995 Model Building for the Cox Proportional Hazards Model with the SAS System Richard Vonk source 12
SUGI 1995 Data about Data: An Introduction to Dictionary Tables Frank C. DiIorio,
Nancy J. Michal		 source 6
NESUG 1994 How MERGE Really Works Bob Virgile 8
NESUG 1994 Validating Your SAS Program Jennifer Dougherty 4
NESUG 1993 Using SAS Macros Functions to Extend the SAS System Sigurd W. Hermansen 7
SCSUG 1993 SAS Puzzlers! Conrad Reynolds 8
SEUGI 1993 A Generic Data Listing System Developed for Pharmaceutical Reporting Peter Fursdon source 11
SESUG 1993 VRANGE: Deriving A Minimal FORMAT from a Numeric Variable's Range of Values Andy Barnett,
CUnical Trials Support		 5
NESUG 1992 Using SAS Dataset Options to Improve Efficiency Clinton S. Rickards 2
SUGI 1992 A SAS Program for Reproducing the Results from the ITEM Procedure Shu-Yeng Wong source 5
NESUG 1991 Using SAS Character and List Functions to Extend the SAS Systems Par I. Data Step Applications Sigurd W. Hermansen 6
SEUGI 1991 Development of PC-based Land Suitability Analysis and Demand Distribution Model for Allocation, Forecasting and Planning Elise Bright,
Parviz Nazem		 source 12
SUGI 1991 Techniques for Improving Coding and Processing Efficiency in the DATA Step Herbert C. Reynolds,
Thomas Jacob		 source 4
SUGI 1991 Using the C Language with SAS/TOOLKIT Software Oliver Bradley source 11
NESUG 1990 How MERGE Really Works Robert Virgile 7
NESUG 1989 Good Code, Bade Code: Strategies for Program Design Frank C. DiIorio 7
SUGI 1989 A Macro to Separate Records into Output Data Sets by Date and Create Data Set Names with Date as a Part Michael J. Schilling source 6
SUGI 1989 A Meta-database Implementation Strategy for Documentation and Retrieval Using the SAS System John Podgurski source 10
SUGI 1989 Index Your Book with the DATA Step Language Jay A. Jaffe source 4
SUGI 1989 The Statistical-Model Toolbox: A SAS Macro System David S. Frankel source 6
SUGI 1988 A Documentation and Retrieval Strategy using the SAS System John Podgurski source 6
SUGI 1988 PROC DICHOT: A SAS Procedure for Creating Dichotomous Variables Paul Lambert source 6
SUGI 1988 PROC TWOSAMPLE A SAS Procedure for the Two-Sample T and Rank-Sum Tests with Extensions Jon L. Kosanke,
Peter C. O'Brien,
Kenneth P. Offord		 source 6
SUGI 1988 Processing Large Files: The SUMMARY Procedure and Other Efficiency Tips Juliana M. Ma source 9
SUGI 1988 SAS/AF Utility Macros Karen Crandall source 3
SEUGI 1987 A Macro for Weighted Moving Averages Leena Metso source 4
SUGI 1987 Using SAS Software Graphical Procedures for the Observer Agreement Chart Shrikant I. Bangdiwala,
Hope E. Bryan		 source 6
SUGI 1985 An Interactive Technique for Copying and Modifying SAS/FSP Screen Data Set Definitions Phil Brennan,
Michael Cushman		 source
SUGI 1985 PROC PECAN - A SAS Procedure Sivaram Kalyandrug,
Jay H. Lubin		 source 8
SUGI 1985 Using PROC COPYLIB to Create a SAS-based Data Dictionary Wayne Beekman source 3
SUGI 1984 New SAS Survival Procedures David M. DeLong source 3
SEUGI 1983 Use of SAS Regression Techniques for Capacity Planning E. M. McCall 9
SUGI 1982 PROCs COMPARE and HEADER for Efficient Database Management in SAS Martha McCrate,
J. Philip Miller,
Michael A. Province		 source 6
SUGI 1981 PROC BACKUP: Creating Raw Data Files from SAS Data Sets David H. Christiansen,
James D. Hosking		 source 6

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