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Richann J. Watson

147 papers and 11 presentations; 75 titles; 30 coauthors.

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Conference × Year × Title × Co-authors Extras Pages
WUSS 2026 A Map to Success with Data Visualization Using ODS Statistical Graphics Louise S. Hadden source 23
WUSS 2026 Take CoMmanD of Your Log: Using CMD to Check Your SAS Program Logs source 12
PharmaSUG 2026 A Map to Success with Data Visualization Using ODS Statistical Graphics Louise S. Hadden source 23
PharmaSUG 2026 ADaM Pet Peeves Part 2: More Things Programmers Do That Make Us Crazy Sandra Minjoe,
Nancy Brucken,
Alyssa Wittle,
Nate Freimark,
Paul K. Slagle,
Tatiana Sotingco
source 15
PharmaSUG 2026 Picking Up the Pieces: Implementation of (the forgotten) ADaM Naming Fragments Karl Miller source 7
PharmaSUG 2026 Take CoMmanD of Your Log: Using CMD to Check Your SAS Program Logs source 12
PharmaSUG 2026 The Tipsy Hangover: Avoiding Indent Headaches in SAS Reports Lisa A. Mendez source 22
SAS Innovate 2026 A Map to Success with Data Visualization Using ODS Statistical Graphics [presentation] Louise S. Hadden source
youtube
PHUSE US 2026 Around the Data DOSE-y Doe: Using DOSExx Variables within ADaM Datasets Inka Leprince source 10
MWSUG 2025 From Muggles to Macros: Transfiguring Your SAS Programs With Dynamic, Data-Driven Wizardry [presentation] Joshua M. Horstman source 52
MWSUG 2025 Have a Date with ISO? Using PROC FCMP to Convert Dates to ISO 8601 source 15
MWSUG 2025 More Muggles, More Macros: Adding Advanced Data-Driven Wizardry to Your SAS Programs [presentation] Joshua M. Horstman source 45
MWSUG 2025 Worried about that Second Date with ISO? Using PROC FCMP to Convert and Impute ISO 8601 Dates to Numeric Dates source 19
SESUG 2025 From Muggles to Macros: Transfiguring Your SAS Programs With Dynamic, Data-Driven Wizardry Joshua M. Horstman 52
SESUG 2025 Have a Date with ISO? Using PROC FCMP to Convert Dates to ISO 8601 15
SESUG 2025 More Muggles, More Macros: Adding Advanced Data-Driven Wizardry to Your SAS Programs Joshua M. Horstman 45
SESUG 2025 Perfect Patient Profiles in SAS using ODS and the Graph Template Language (GTL) Joshua M. Horstman 38
SESUG 2025 Worried about that Second Date with ISO? Using PROC FCMP to Convert and Impute ISO 8601 Dates to Numeric Dates 19
WUSS 2025 Around the Data DOSE-y Doe, How Much Fun Can Your Data Can Be: Using DOSExx Variables within ADaM Data Sets Inka Leprince source 13
WUSS 2025 From Muggles to Macros: Transfiguring Your SAS Programs With Dynamic, Data-Driven Wizardry [presentation] Joshua M. Horstman source 52
WUSS 2025 Have a Date with ISO? Using PROC FCMP to Convert Dates to ISO 8601 source 15
WUSS 2025 More Muggles, More Macros: Adding Advanced Data-Driven Wizardry to Your SAS Programs [presentation] Joshua M. Horstman source 45
WUSS 2025 Worried about that Second Date with ISO? Using PROC FCMP to Convert and Impute ISO 8601 Dates to Numeric Dates source 19
PharmaSUG 2025 Advanced Programming with R: Leveraging Tidyverse and Admiral for ADaM Dataset Creation with a Comparison to SAS Joshua J. Cook source 20
PharmaSUG 2025 Get Tipsy with Debugging Tips for SAS Code: The After Party Lisa A. Mendez source 16
PharmaSUG 2025 Worried about that Second Date with ISO? Using PROC FCMP to Convert and Impute ISO 8601 Dates to Numeric Dates source 19
SAS Innovate 2025 More Muggles, More Macros: Adding Advanced Data-Driven Wizardry to Your SAS Programs [video] Joshua M. Horstman source
video
MWSUG 2024 Adventures in Independent Consulting: Perspectives from Two Veteran Consultants Living the Dream Joshua M. Horstman source 7
MWSUG 2024 Complex Custom Clinical Graphs Step by Step with SAS ODS Statistical Graphics [presentation] Joshua M. Horstman source 44
MWSUG 2024 From Muggles to Macros: Transfiguring Your SAS Programs With Dynamic, Data-Driven Wizardry [presentation] Joshua M. Horstman source 52
MWSUG 2024 Just Stringing Along: FIND Your Way to Great User-Defined Functions Louise S. Hadden source 10
MWSUG 2024 What's Your Favorite Color? Controlling the Appearance of a Graph source 33
SESUG 2024 Adventures in Independent Consulting: Perspectives from Two Veteran Consultants Living the Dream Joshua M. Horstman source 7
SESUG 2024 Complex Custom Clinical Graphs Step by Step with SAS ODS Statistical Graphics Joshua M. Horstman source 44
SESUG 2024 From Muggles to Macros: Transfiguring Your SAS Programs With Dynamic, Data-Driven Wizardry Joshua M. Horstman source 52
SESUG 2024 Just Stringing Along: FIND Your Way to Great User-Defined Functions Louise S. Hadden source 9
SESUG 2024 The Battle of the Titans: DATA Step versus PROC SQL Kirk Paul Lafler,
Charu Shankar,
Joshua M. Horstman
source 22
WUSS 2024 From Muggles to Macros: Transfiguring Your SAS Programs With Dynamic, Data-Driven Wizardry [presentation] Joshua M. Horstman source 52
WUSS 2024 Just Stringing Along: FIND Your Way to Great User-Defined Functions Louise S. Hadden source 10
WUSS 2024 LAST CALL to Get Tipsy with SAS: Tips for Using CALL Subroutines Lisa A. Mendez source 20
PharmaSUG 2024 Around the Data DOSE-y Doe, How Much Fun Can Your Data Can Be: Using DOSExx Variables within ADaM Data Sets Inka Leprince source 12
PharmaSUG 2024 Complex Custom Clinical Graphs Step by Step with SAS ODS Statistical Graphics Joshua M. Horstman source 44
PharmaSUG 2024 Exploit the Window of Opportunity: Exploring the Use of Analysis Windowing Variables Elizabeth Dennis,
Karl Miller
source 4
PharmaSUG 2024 Just Stringing Along: FIND Your Way to Great User-Defined Functions Louise S. Hadden source 9
PharmaSUG 2024 LAST CALL to Get Tipsy with SAS: Tips for Using CALL Subroutines Lisa A. Mendez source 20
WUSS 2023 10 Quick Tips for Getting Tipsy with SAS Lisa A. Mendez source 16
WUSS 2023 Adventures in Independent Consulting: Perspectives from Two Veteran Consultants Living the Dream Joshua M. Horstman source 7
WUSS 2023 Going Command(o): Power(Shell)ing Through Your Workload Louise S. Hadden source 45
WUSS 2023 Great Time to Learn GTL Kriss Harris source 12
WUSS 2023 Let's Get FREQy with our Statistics: Data-Driven Approach to Determining Appropriate Test Statistic Lynn Mullins source 14
WUSS 2023 The Battle of the Titans: DATA Step versus PROC SQL Kirk Paul Lafler,
Joshua M. Horstman,
Charu Shankar
source 22
WUSS 2023 When ANY Function Will Just NOT Do Karl Miller source 8
SESUG 2023 10 Quick Tips for Getting Tipsy with SAS Lisa A. Mendez source 16
SESUG 2023 Going Command(o): Power(Shell)ing Through Your Workload Louise S. Hadden source 45
SESUG 2023 The Battle of the Titans: DATA Step versus PROC SQL Kirk Paul Lafler,
Joshua M. Horstman,
Charu Shankar
source 22
PharmaSUG 2023 10 Quick Tips for Getting Tipsy with SAS Lisa A. Mendez source 16
PharmaSUG 2023 Adventures in Independent Consulting: Perspectives from Two Veteran Consultants Living the Dream Joshua M. Horstman source 7
PharmaSUG 2023 Going Command(o): Power(Shell)ing Through Your Workload Louise S. Hadden source 45
PharmaSUG 2023 Have a Date with ISO? Using PROC FCMP to Convert Dates to ISO 8601 source 15
PharmaSUG 2023 Have Meaningful Relationships: An Example of Implementing SDTM Special Purpose Data Set RELREC with a Many-to-Many Relationship Kaleigh Ragan source 11
SESUG 2022 Adventures in Independent Consulting: Perspectives from Two Veteran Consultants Living the Dream Joshua M. Horstman source 7
SESUG 2022 Functions (and More!) on CALL! Louise S. Hadden source 33
SESUG 2022 Have a Date with ISO? Using PROC FCMP to Convert Dates to ISO 8601 source 15
SESUG 2022 Standardized, Customized or Both? Defining and Implementing (MedDRA) Queries in ADaM Data Sets Karl Miller source 7
SESUG 2022 What's Your Favorite Color? Controlling the Appearance of a Graph source 33
SAS Explore 2022 These are a Few of Our Favorite SAS Functions [video] Louise S. Hadden source
youtube
WUSS 2022 "Bored"-Room Buster Bingo - Create Bingo Cards Using SAS ODS Graphics Louise S. Hadden source 32
WUSS 2022 Adventures in Independent Consulting: Perspectives from Two Veteran Consultants Living the Dream Joshua M. Horstman source 7
WUSS 2022 Child Data Set: An Alternative Approach for Analysis of Occurrence and Occurrence of Special Interest Lindsey Xie,
Jinlin Wang,
Lauren Xiao
source 15
WUSS 2022 Functions (and More!) on CALL! Louise S. Hadden source 33
WUSS 2022 Have a Date with ISO? Using PROC FCMP to Convert Dates to ISO 8601 source 15
WUSS 2022 Standardised MedDRA Queries (SMQs): Beyond the Basics; Weighing Your Options Karl Miller source 8
WUSS 2022 Standardized, Customized or Both? Defining and Implementing (MedDRA) Queries in ADaM Data Sets Karl Miller source 7
WUSS 2022 What Kind of WHICH Do You CHOOSE to be? Louise S. Hadden source 7
WUSS 2022 What's Your Favorite Color? Controlling the Appearance of a Graph source 33
PharmaSUG 2022 ADaM Child Data Set: An Alternative Approach for Analysis of Occurrence and Occurrence of Special Interest Lindsey Xie,
Jinlin Wang,
Lauren Xiao
source 15
PharmaSUG 2022 Functions (and More!) on CALL! Louise S. Hadden source 33
PharmaSUG 2022 Standardised MedDRA Queries (SMQs): Beyond the Basics; Weighing Your Options Karl Miller source 8
SESUG 2021 "Bored"-Room Buster Bingo - Create Bingo Cards Using SAS ODS Graphics Louise S. Hadden source 12
SESUG 2021 What Kind of WHICH Do You CHOOSE to be? Louise S. Hadden source 7
PharmaSUG 2021 "Bored"-Room Buster Bingo - Create Bingo Cards Using SAS ODS Graphics Louise S. Hadden source 12
PharmaSUG 2021 What Kind of WHICH Do You CHOOSE to be? Louise S. Hadden source 7
SGF 2021 Quick, Call the "FUZZ": Using Fuzzy Logic Louise S. Hadden source 30
SGF 2021 What Kind of WHICH Do You CHOOSE to be? Louise S. Hadden source 7
SGF 2020 What's Your Favorite Color? Controlling the Appearance of a Graph source 33
PharmaSUG 2020 Are you Ready? Preparing and Planning to Make the Most of your Conference Experience Louise S. Hadden source 15
PharmaSUG 2020 Great Time to Learn GTL: A Step-by-Step Approach to Creating the Impossible source 26
PharmaSUG 2020 Quick, Call the "FUZZ": Using Fuzzy Logic Louise S. Hadden source 30
PharmaSUG 2020 What's Your Favorite Color? Controlling the Appearance of a Graph source 33
PHUSE EU 2019 Interactive Graphs Kriss Harris source
presentation source
11
SESUG 2019 Great Time to Learn GTL: A Step-by-Step Approach to Creating the Impossible source 26
SESUG 2019 Quick, Call the "FUZZ": Using Fuzzy Logic source 30
MWSUG 2019 Are you Ready? Preparing and Planning to Make the Most of your Conference Experience Louise S. Hadden 15
MWSUG 2019 Interactive Graphs Kriss Harris 24
MWSUG 2019 Quick, Call the "FUZZ": Using Fuzzy Logic Louise S. Hadden 30
WUSS 2019 Are you Ready? Preparing and Planning to Make the Most of your Conference Experience source 15
WUSS 2019 Great Time to Learn GTL: A Step-by-Step Approach to Creating the Impossible source 26
WUSS 2019 Interactive Graphs Kriss Harris source 24
PharmaSUG 2019 Interactive Graphs Kriss Harris source 24
PharmaSUG 2019 Making Lab Toxicity Tables Less Toxic on Your Brain Lindsey Xie,
Jinlin Wang,
Jennifer Sun,
Rita Lai
source 13
PharmaSUG 2019 More Traceability: Clarity in ADaM Metadata and Beyond Wayne Zhong,
Daphne E. Ewing,
Jasmine Zhang
source 26
PharmaSUG 2019 Tips from Three Business Owners Robert Howard,
Joshua M. Horstman
source 6
SGF 2019 Great Time to Learn GTL: A Step-by-Step Approach to Creating the Impossible source 26
SGF 2019 Interactive Graphs Kriss Harris source 23
SCSUG 2018 'V' for ... Variable Information Functions to the Rescue Karl Miller source 16
SCSUG 2018 Animate Your Data! Kriss Harris source 18
SCSUG 2018 Automated Validation of Complex Clinical Trials Made Easy source 35
SCSUG 2018 Let SAS Do Your DIRty Work source 8
SCSUG 2018 Using a Picture Format to Create Visit Windows source 5
PHUSE EU 2018 Animate Your Data! Kriss Harris source
presentation source
14
SESUG 2018 Animate Your Data! Kriss Harris source 18
SESUG 2018 Let's Get FREQy with our Statistics: Data-Driven Approach to Determining Appropriate Test Statistic Lynn Mullins source 14
SESUG 2018 Using a Picture Format to Create Visit Windows source 5
MWSUG 2018 Animate Your Data! Kriss Harris 18
MWSUG 2018 Avoiding Sinkholes: Common Mistakes During ADaM Data Set Implementation 15
MWSUG 2018 Great Time to Learn GTL Kriss Harris 12
WUSS 2018 Animate Your Data! Kriss Harris source 18
WUSS 2018 Great Time to Learn GTL Kriss Harris source 12
WUSS 2018 Let's Get FREQy with our Statistics: Data-Driven Approach to Determining Appropriate Test Statistic Lynn Mullins source 14
PharmaSUG 2018 Automated Validation of Complex Clinical Trials Made Easy Joshua M. Horstman source 35
PharmaSUG 2018 Avoiding Sinkholes: Common Mistakes During ADaM Data Set Implementation Karl Miller source 18
PharmaSUG 2018 Great Time to Learn GTL Kriss Harris source 12
PharmaSUG 2018 Let's Get FREQy with our Statistics: Data-Driven Approach to Determining Appropriate Test Statistic Lynn Mullins source 14
PharmaSUG 2018 Traceability: Some Thoughts and Examples for ADaM Needs Kent Letourneau,
Wayne (Weizhen) Zhong,
Sandra Minjoe
source 18
SGF 2018 Animate Your Data! Kriss Harris source 15
SGF 2018 Let's Get FREQy with our Statistics: Data-Driven Approach to Determining Appropriate Test Statistic [presentation] Lynn Mullins source 24
SGF 2018 V is for Venn Diagrams Kriss Harris source 22
SESUG 2017 Automated Validation of Complex Clinical Trials Made Easy source 35
SESUG 2017 Let SAS Do Your DIRty Work source 8
SESUG 2017 When ANY Function Will Just NOT Do source 8
MWSUG 2017 Automated Validation of Complex Clinical Trials Made Easy Joshua M. Horstman 35
MWSUG 2017 Exploring HASH Tables vs. SORT/DATA Step vs. PROC SQL Lynn Mullins 14
MWSUG 2017 Let's Get FREQy with our Statistics: Let SAS Determine the Appropriate Test Statistic Based on Your Data Lynn Mullins 14
WUSS 2017 Automated Validation of Complex Clinical Trials Made Easy Joshua M. Horstman source 34
WUSS 2017 Avoiding Sinkholes: Common Mistakes During ADaM Data Set Implementation Karl Miller source 15
PharmaSUG 2017 Check Please: An Automated Approach to Log Checking source 12
PharmaSUG 2017 Standardized, Customized or Both? Defining and Implementing (MedDRA) Queries in ADaM Data Sets Karl Miller source 7
SGF 2017 Check Please: An Automated Approach to Log Checking source 12
SGF 2017 Let SAS Do Your DIRty Work source 8
SGF 2017 When ANY Function Will Just NOT Do Karl Miller source
pdf
8
MWSUG 2016 When ANY Function Will Just NOT Do Karl Miller 1
WUSS 2016 Check Please: An Automated Approach to Log Checking source 10
WUSS 2016 Let SAS Do Your DIRty Work source 6
PharmaSUG 2016 Exploring HASH Tables vs. SORT/DATA Step vs. PROC SQL Lynn Mullins source 14
PharmaSUG 2016 When ANY Function Will Just NOT Do Karl Miller source 8
MWSUG 2015 'V' for ... Variable Information Functions to the Rescue Karl Miller 16
MWSUG 2015 Using a Picture Format to Create Visit Windows 4
PharmaSUG 2015 Considerations in ADaM Occurrence Data: Handling Crossover Records for Non-Typical Analysis Karl Miller source 6
PharmaSUG 2015 Proper Parenting: A Guide in Using ADaM Flag/Criterion Variables and When to Create a Child Dataset Karl Miller,
Paul K. Slagle
source 10
MWSUG 2014 'V' for ... Variable Information Functions to the Rescue Karl Miller 16
PharmaSUG 2014 'V' for ... Variable Information Functions to the Rescue Karl Miller source 15
MWSUG 2013 Let SAS Do Your DIRty Work 7
PharmaSUG 2013 Let SAS Do Your DIRty Work source 7
MWSUG 2012 Using a Picture Format to Create Visit Windows 4
PharmaSUG 2012 Using a Picture Format to Create Visit Windows source 4
MWSUG 2011 Automated or Manual Validation: Which One is for You? Patty Johnson 5
PharmaSUG 2011 Automated or Manual Validation: Which One is for You? Patty Johnson source 5
PharmaSUG 2004 Generating Least Square Means, Standard Error, Observed Mean, Standard Deviation and Confidence Intervals for Treatment Differences using Proc Mixed 12

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