WUSS 2022 Virtual Encores

WUSS 2022 Virtual Encores

Western Users of SAS Software is excited to announce WUSS 2022 Virtual Encores, a curated selection of the finest content from the wildly successful WUSS 2022 conference held last fall in San Francisco. If you couldn’t attend last fall, or even if you did and you just can’t wait until October 2023 to get more WUSS, WUSS 2022 Virtual Encores has something for everyone!

WUSS 2022 Virtual Encores features several of our most popular half-day training classes taught by seasoned industry experts. These classes are a tremendous value at just $150 per class. All classes are held from 10am to 2pm PT (1pm to 5pm ET).

Register Now

Registration is NOW OPEN for all classes! Please click on each class title for a detailed description of the course and information about the instructors.

Date Course Title (click for description) Instructor(s)
(click for bio)
FEBRUARY 2023
Feb 22 From %MACRO to %MEND: Getting Started with SAS Macro Language Basics – Part 1 Josh Horstman
Feb 23 From %MACRO to %MEND: Getting Started with SAS Macro Language Basics – Part 2 Josh Horstman
MARCH 2023
Mar 2 CDISC ADaM – Implementation by Example (HOW*) Richann Watson
Mar 3 Everything is Better with Friends: Using SAS in Python Applications with SASPy and Open-Source Tooling – Getting Started (HOW*) Isaiah Lankham
& Matthew Slaughter
Mar 9 CDISC ADaM – Principles, Rules and Complex Examples (HOW*) Richann Watson
Mar 10 Everything is Better with Friends: Using SAS in Python Applications with SASPy and Open-Source Tooling – Beyond the Basics (HOW*) Isaiah Lankham
& Matthew Slaughter
Mar 15 Data Analytics: Concepts, Challenges, and Solutions Using SAS® Kirk Lafler
Mar 29 Custom Excel Reports and Spreadsheets Using PROC REPORT and the ODS Excel Destination Kirk Lafler
APRIL 2023
Apr 11 SAS + R Part 1: Connecting SAS and R in Your Data Science Workflow Hunter Glanz
Apr 18 SAS + R Part 2: Using R Shiny to Make Your Data Wrangling and Visualization Interactive Hunter Glanz

*HOW = Hands-on Workshop. These courses will feature instructor-led exercises that can be completed in class.


Register Now



Course Descriptions

From %MACRO to %MEND: Getting Started with SAS Macro Language Basics – Part 1
Josh Horstman
Wednesday, February 22, 2023
10:00 AM – 2:00 PM Pacific Time

This two-part seminar is designed for the SAS programmer who is new to the Macro Language. We will start with the basics and cover the fundamentals necessary to start applying SAS macros in your programs. Part 1 covers how the Macro Language works, what the Macro Symbol Table is and how to store values in it, how the SAS System uses Macro Variables, calling and executing macros, using macro parameters, and other key Macro Language concepts. It is intended to be paired with Part 2 for a complete foundation in the macro language.

Back to top


From %MACRO to %MEND: Getting Started with SAS Macro Language Basics – Part 2
Josh Horstman
Thursday, February 23, 2023
10:00 AM – 2:00 PM Pacific Time

This two-part seminar is designed for the SAS programmer who is new to the Macro Language. We will start with the basics and cover the fundamentals necessary to start applying SAS macros in your programs. Building on the foundational concepts of the first part, Part 2 covers how to control your SAS programs with macros, the use of key SAS Macro Language statements, interfacing with data values in the macro language, macro functions, macro language arithmetic, and other fundamental macro language concepts. Using examples, this course demonstrate the power and flexibility of this part of the SAS System and will enable you to apply its functionalities to your own programs right away.

Back to top


CDISC ADaM – Implementation by Example (HOW)
Richann Watson
Thursday, March 2, 2023
10:00 AM – 2:00 PM Pacific Time

This course will provide a high-level overview of some of basic ADaM concepts. It is assumed that the attendee will have a fundamental knowledge of the different ADaM structures and principles. The primary focus of the course is to illustrate the implementation of some of the concepts found in both the ADaM Implementation Guide (ADaM IG) and the ADaM Structure for Occurrence Data (OCCDS) documents. Items covered include setting up subject level analysis data set (ADSL) for common trial designs and walking through the process of creating a basic data structure (BDS) starting from a simple BDS and building on it to structure a data set that will support one or more analyses. Additionally, the course will demonstrate how to implement some variables that are only found in OCCDS, such as the standardized MedDRA query (SMQ) and customized query (CQ) variables. This course is billed as a “lecture” style course; however, exercises will be provided to attendees in Adobe PDF format, so a laptop with Adobe Reader installed will be highly beneficial for attendees.

Back to top


Everything is Better with Friends: Using SAS in Python Applications with SASPy and Open-Source Tooling – Getting Started (HOW*)
Isaiah Lankham, Matthew Slaughter
Friday, March 3, 2023
10:00 AM – 2:00 PM Pacific Time

Interested in learning Python? How about learning to make Python and SAS work together? In this hands-on class, we’ll practice writing Python scripts in Google Colab (an online implementation of JupyterLab). These Python scripts will link to SAS OnDemand for Academics using the Python package SASPy developed by SAS Institute. We’ll also practice using the popular Python package pandas, whose DataFrame objects are the Python equivalent of SAS datasets. Along the way, we’ll work through common data-analysis tasks using both regular SAS code and Python together with the SASPy package, highlighting important tradeoffs for each and emphasizing the value of being a polyglot programmer fluent in multiple languages. This will include a beginner-friendly overview of Python syntax and data structures. This class is aimed at SAS programmers of all skill levels, including those with no prior experience using Python or JupyterLab. However, some examples will assume familiarity with the Output Delivery System, PROC SQL, and the SAS Macro Facility. Accounts for Google and SAS OnDemand for Academics will be needed to interact with code examples. All class materials, including complete setup instructions, will be made available through https://github.com/saspy-bffs/wuss-2022-virtual-encores. This is the first class in a two-part series. Each part may be taken individually or as a package.

Back to top


CDISC ADaM – Principles, Rules and Complex Examples (HOW)
Richann Watson
Thursday, March 9, 2023
10:00 AM – 2:00 PM Pacific Time

This course will provide a high-level overview of some of the basic ADaM concepts; however, it is assumed that the attendee will be familiar with the different ADaM structures and principles. The course will delve into what is meant by traceability and analysis ready as well as look at some rules and best practices. However, the primary focus is to illustrate the implementation of some of the more difficult or less common concepts found in both the ADaM Implementation Guide (ADaMIG) and the ADaM Structure for Occurrence Data (OCCDS) documents. The course includes an illustration of the use of criterion variables (CRITy and MCRITy) and record-level and parameter-level population flags (-RFL and -PFL), as well as a demonstration of how to set up time-to-event and questionnaire/rating/scales analysis data sets. In addition, it will go into depth about AEs of special interest and the use of Standard MedDRA Queries (SMQ) and provide an illustration of how the OCCDS can be used to handle the non-typical analysis for events data. This course is billed as a “lecture” style course; however, exercises will be provided to attendees in Adobe PDF format, so a laptop with Adobe Reader installed will be highly beneficial for attendees.

Back to top


Everything is Better with Friends: Using SAS in Python Applications with SASPy and Open-Source Tooling – Beyond the Basics (HOW*)
Isaiah Lankham, Matthew Slaughter
Friday, March 10, 2023
10:00 AM – 2:00 PM Pacific Time

Are you familiar with Python syntax? Want to go beyond the basics, and use SAS and Python together like a pro? As in the “Getting Started” version of this course, we’ll practice writing Python scripts in Google Colab (an online implementation of JupyterLab). These Python scripts will link to SAS OnDemand for Academics using the Python package SASPy developed by SAS Institute. We’ll also practice using the popular Python package pandas, whose DataFrame objects are the Python equivalent of SAS datasets. Along the way, we’ll work through common data-analysis tasks using both regular SAS code and Python together with the SASPy package, highlighting important tradeoffs for each and emphasizing the value of being a polyglot programmer fluent in multiple languages. Specific examples include advanced data-manipulation techniques, using SASPy as an interface for SAS/STAT, rectangularizing complex JSON-formatted data returned by web APIs, and creating simple Python web applications incorporating SAS analytics. This class is aimed at intermediate to advanced SAS programmers, but assumes only basic familiarity with Python syntax and pandas DataFrames. However, no knowledge of JupyterLab is assumed. Accounts for Google and SAS OnDemand for Academics will be needed to interact with code examples. All class materials, including complete setup instructions, will be made available through https://github.com/saspy-bffs/wuss-2022-virtual-encores. This is the second class in a two-part series. Each part may be taken individually or as a package.

Back to top


Data Analytics: Concepts, Challenges, and Solutions Using SAS®
Kirk Lafler
Wednesday, March 15, 2023
10:00 AM – 2:00 PM Pacific Time

Data is ubiquitous. With 2.5 quintillion bytes (1 with 18 zeros) of new data being created each day, data literacy – the ability to analyze and interpret data – is an increasingly valuable skill, particularly in the age of big data. Organizations across industries are embracing data analytics resulting in a growing demand for qualified and experienced talent with essential data and analysis skills. Data analytics is the process and practice of analyzing data to identify trends, extract insights, answer questions, and help understand things that were learned that could negate or call into question the assumptions going into the analysis. This course introduces concepts, challenges, and solutions associated with the data ecosystem and data analytics lifecycle’s steps: data collection / extraction, cleaning / transformation, analysis, visualization, and interpretation. Attendees explore the different types of data: quantitative versus qualitative; the data measurement scale: nominal, ordinal, interval, and ratio; data file types; data collection / extraction techniques; data cleaning / transformation techniques; Descriptive, Diagnostic, Predictive, and Prescriptive analytics techniques; visualization techniques; and interpretation techniques using SAS® software.

Download a detailed course description (PDF, 189K).

Back to top


Custom Excel Reports and Spreadsheets Using PROC REPORT and the ODS Excel Destination
Kirk Lafler
Wednesday, March 29, 2023
10:00 AM – 2:00 PM Pacific Time

SAS® users everywhere turn to the REPORT procedure to customize and satisfy their reporting needs as they create and deliver quality “custom” detail and summary reports, and specialized output for management, end users, and customers. This popular course explores an assortment of techniques to create custom spreadsheets, reports and specialized output using PROC REPORT and the powerful ODS Excel destination. Attendees learn how to create detail and summary spreadsheets, reports and output using PROC REPORT; acquire useful Output Delivery System (ODS) skills; combine PROC REPORT and the powerful ODS Excel destination to produce quick and formatted detail and summary Excel workbook results; customize output and results with SAS-supplied styles; compute subtotals and totals at the end of a report using a COMPUTE Block; calculate percentages; produce statistics for analysis variables; apply conditional logic to control summary output rows; add background images; build custom autofilter drill-down (interactive) reports and Excel workbooks; and add traffic lighting scenarios to Excel workbooks.

Back to top


SAS + R Part 1: Connecting SAS and R in Your Data Science Workflow
Hunter Glanz
Tuesday, April 11, 2023
10:00 AM – 2:00 PM Pacific Time

As robust statistical software packages, SAS and R boast a great number of tools for addressing all of your data-related needs. While there exists large overlap in what they provide, today’s statistical and data science problems increasingly involve multiple software packages. After all, if you have access to all of these tools then why not explore how they can improve your workflow! In this class we will explore the complete workflow of cleaning a dataset, exploring it, visualizing it using a combination of SAS and R.

Back to top


SAS + R Part 2: Using R Shiny to Make Your Data Wrangling and Visualization Interactive
Hunter Glanz
Tuesday, April 18, 2023
10:00 AM – 2:00 PM Pacific Time

While both SAS and R include a rich suite of tools for working with your data, there often exists a collection of tasks and activities that get repeated with every new dataset. Traditionally such repetition could be addressed by building macros or functions. R Shiny enhances this process by making your data work interactive! Not only can this save you some code and work, but it provides a way for consumers of your work to do all of your cool data science-y things without needing to know how to program. In this class we will build our very own basic shiny applications using R.

Back to top


Meet the Instructors

Hunter Glanz is an Associate Professor of Statistics and Data Science at California Polytechnic State University (Cal Poly, San Luis Obispo). He received a BS in Mathematics and a BS in Statistics from Cal Poly, San Luis Obispo followed by an MA and PhD in Statistics from Boston University. He maintains a passion for machine learning and statistical computing, and enjoys advancing education efforts in these areas. In particular, Cal Poly’s courses in R, SAS, and Python give him the opportunity to connect students with exciting data science topics amidst a firm grounding in communication of statistical ideas. Hunter serves on numerous committees and organizations dedicated to delivering cutting edge statistical and data science content to students and professionals alike. In particular, the ASA’s DataFest event at UCLA has been an extremely rewarding experience for the teams of Cal Poly students Hunter has had the pleasure of advising.

Back to top

Josh Horstman is an independent statistical programmer based in Indianapolis with over 20 years’ experience using SAS in the life sciences industry. He specializes in analyzing clinical trial data, and his clients have included major pharmaceutical corporations, biotech companies, and research organizations. A SAS Certified Advanced Programmer, Josh loves coding and is a frequent presenter and trainer at SAS user conferences. Josh holds a bachelor’s degree in mathematics and computer science, and a master’s degree in statistics from Colorado State University.

Back to top

Kirk Paul Lafler is a SAS, SQL and Python programmer, application developer and consultant. He teaches at San Diego State University and the University of California San Diego Extension as a lecturer and adjunct professor; and is an author of several books including, PROC SQL: Beyond the Basics Using SAS, Third Edition. Kirk has served as an Invited speaker, educator, keynote and section leader at SAS conferences for 40 years, and is the recipient of 27 “Best” contributed paper, hands-on workshop (HOW), and poster awards.

Back to top

Isaiah Lankham specializes in data analysis using Tableau, SAS, and Python, currently serving as a research analyst for the Kaiser Permanente Center for Health Research in Portland, Oregon. Initially trained as a mathematician and educator, Isaiah is also an adjunct faculty member for the Statistics Department at California State University, East Bay, and enjoys regularly teaching graduate SAS programming courses.

Back to top

Matthew T. Slaughter, MSBA is an Advanced SAS Certified Programmer and a Data Scientist at the Kaiser Permanente Center for Health Research in Portland, Oregon. With a focus on clinical prediction modeling, Matthew provides data management, programming, and analytical support to research projects in various topic areas.

Back to top

Richann Watson is an independent statistical programmer and CDISC consultant based in Ohio. She has been using SAS since 1996 with most of her experience being in the life sciences industry. She specializes in analyzing clinical trial data and implementing CDISC standards. Additionally, she is a member of the CDISC ADaM team and various sub-teams.

Richann loves to code and is an active participant and leader in the SAS User Group community. She has presented numerous papers, posters, and training seminars at SAS Global Forum, PharmaSUG, and various regional and local SAS user group meetings. Richann holds a bachelor’s degree in mathematics and computer science from Northern Kentucky University and master’s degree in statistics from Miami University.

Back to top