MidWest SAS Users Group - Training Seminars

Proceedings

Get Updates

MWSUG 2019 Training Classes

Customize Your Own Training Curriculum

MWSUG offers a full menu of pre-conference training courses. These training classes are learning opportunities which allow you to delve more deeply into a topic. Classes are offered on the Friday, Saturday, and Sunday prior to the conference. Training is located on the Third Floor of the West Tower of the Hyatt Regency Chicago.

Any of our courses are open to any person who wants to take them. To help you, we have grouped the courses into “tracks” related to your interests. For example, if you are a Clinical Programmer, you might be interested in the courses in the first column. If you are, or are learning to be, a Statistician or Data Scientist, the courses in the 4th column might be of interest.

Note that there are courses with some overlapping content. You can take all of them and get a deeper introduction into the topics. You can also combine some of these with other courses to broaden your skills.

You may mix and match courses however you like to suit your needs. Discounts are available when you take multiple classes (see below for fees). Take advantage of this opportunity to build your own custom training curriculum!

Course Schedule

Click on the course title for a short description. Click on the instructor name(s) for biographical information.

Friday, September 27, 2019

Time	Room 1 - Clinical (McCormick)	Room 2 - Beginner (Wright)	Room 3 - Intermediate (Field)	Room 4 - Statistics (Burnham)
8am - Noon	Introductory ADaM Dataset Development: ADSL, OCCDS and BDS Nancy Brucken & Mario Widel	Getting Started with SAS Macro Language Basics Josh Horstman	Advanced PROC SQL Concepts and Programming Techniques Using SAS® Kirk Lafler	Logistic Regression, Basics and Beyond Bruce Lund
1pm - 5pm	Advanced ADaM Dataset Development: Beyond the ADaMIG Nancy Brucken & Mario Widel	Custom Excel Spreadsheets Using PROC REPORT and the ODS Excel Destination Kirk Lafler	SAS Data-Driven Development – Designing More Flexible, Reusable, Configurable, Maintainable Software Troy Hughes	Logistic Regression for Ordinal and Multinomial Data Bruce Lund

Saturday, September 28, 2019

Time	Room 1 - Reporting (McCormick)	Room 2 - Beginner (Wright)	Room 3 - Intermediate (Field)	Room 4 - Statistics (Burnham)
8am - Noon	Getting Started with PROC REPORT: Understanding the Building Blocks Richann Watson	Intentionally Blank	Building High-Impact Dashboards Using SAS® Base Software Kirk Lafler & Josh Horstman	Regression Expression! 24 Regression Methods in SAS: Part 1 David Corliss
1pm - 5pm	Advanced PROC REPORT: Understanding the Compute Block and the Report Process Richann Watson	Powerful PROC SQL Programming Techniques for SAS® Users and Programmers Kirk Lafler	Advanced SAS Macro Language Techniques for Building Dynamic Programs Josh Horstman	Regression Expression! 24 Regression Methods in SAS: Part 2 David Corliss

Sunday, September 29, 2019

Time	Room 1 - Graphics (McCormick)	Room 2 - Beginner (Wright)	Room 3 - Intermediate (Field)	Room 4 - Statistics (Ogden)
8am - Noon	ODS Graphics I: Creating Quick and Easy Graphs with the Statistical Graphics (SG) Procedures Josh Horstman	Manipulating Data with DO Loops and Arrays Ben Cochran	Macros for the Smart Programmer Stephanie Thompson	Statistics 101: Introduction to Statistical Principles and Quantitative Analytics using SAS/STAT® Michael Wilson
1pm - 5pm	ODS Graphics II: Mastering Custom Graphs with Graph Template Language (GTL) Richann Watson	What Can PROC SQL Do for You? Stephanie Thompson	Express Yourself with Python in SAS Charu Shankar	Modern Regression Techniques Peter Flom

Course Fees and Registration

Registration Type	Half Day	Full Day	Two Day Bundle	Three Day Bundle - BEST VALUE!
Conference Attendee	$175	$350	$650	$945
Without Conference	$275	$550	$1,000	$1,440
Full-Time Student	$100	$200	N/A	N/A

To register for a training class, please select the corresponding class during the registration process. Seating for the training classes are limited and registration will be accepted on a first-come, first-served basis. The two or three day bundle price may be used for any combination of training courses equivalent to two or three full days (four or six half days, respectively).

To take advantage of the bundle pricing, you will need a coupon code. Please email the registrar at This email address is being protected from spambots. You need JavaScript enabled to view it. with a list of the courses you are registering for. After your courses are verified, you will be emailed a coupon code to be used to complete your registration.

Course Descriptions

Introductory ADaM Dataset Development: ADSL, OCCDS and BDS
Nancy Brucken, Mario Widel
Friday, September 27, 2019, 8:00 AM - 12:00 PM, Location: McCormick

This half-day seminar introduces attendees to CDISC ADaM and the ADaM documents. We will discuss how ADaM fits into the clinical process, and describe the key principles of ADaM. We will cover how to apply the basic ADaM concepts, rules, recommended best practices, and the four types of ADaM metadata. The seminar then explains the ADSL, OCCDS and BDS models. Submission deliverables like ADRG and ADaM define.xml will be discussed as well. A basic understanding of SDTM and regulatory submission needs is expected.

Getting Started with SAS Macro Language Basics
Josh Horstman
Friday, September 27, 2019, 8:00 AM - 12:00 PM, Location: Wright

This half-day seminar is designed for the SAS programmer who is new to the Macro Language. We will start at the basics and cover the fundamentals necessary to start applying SAS macros in your programs. By the end of the course you will understand 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, key Macro Language concepts, important SAS Macro Language statements, and how to invoke Macros in your programs. The examples shown in the course materials 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.

Advanced PROC SQL Concepts and Programming Techniques Using SAS®
Kirk Lafler
Friday, September 27, 2019, 8:00 AM - 12:00 PM, Location: Field

Structured Query Language (SQL) is a universal language used in data science, data analytics, statistics, data management, and other disciplines to access, transform, manipulate and output data stored in SAS data sets, relational databases and tables. Based on Kirk’s new Third Edition PROC SQL: Beyond the Basics Using SAS®, this half-day course presents core concepts and programming techniques to help leverage PROC SQL as a programming and database language.

Attendees learn how to construct powerful and scalable queries; construct real-world queries including nearest neighbor and first, last and between By-group processing; apply rule-based and cost-based optimization strategies – influencing the SQL optimizer to choose from the available join algorithms; apply effective “fuzzy” matching programming techniques when a table’s key(s) is (are) inconsistent or less than reliable; use the SQL-macro interface to create single-value (or aggregate) and value-list macro variables; construct effective simple and composite indexes to dynamically access a table’s data; construct table validation rules using table integrity constraints; and explore “select” query performance tuning techniques for big data environments.

Logistic Regression, Basics and Beyond
Bruce Lund
Friday, September 27, 2019, 8:00 AM - 12:00 PM, Location: Burnham

This class presents light theory, supported by simulations, as well as practical suggestions for understanding and developing binary logistic regression models. Topics include: Binary response model overview, the logistic regression model as implemented by SAS® PROC LOGISTIC, the likelihood function, properties of predictor and model fit statistics, Firth method versus maximum likelihood method, screening, binning, transforming of nominal, ordinal, discrete, and continuous predictors, identification of multicollinearity, oversampling for rare events, predictor variable selection methods using PROC LOGISTIC, HPLOGISTIC, HPGENSELECT including Best Subsets, SBC, Lasso, and Validation methods, and measures of fit and predictive accuracy including c statistic, KS statistic, classification error, and lift charts in the context of training, cross-validation and validation samples. Additional: PROC SURVEYLOGISTIC is not discussed. The cumulative logit model and the multinomial logistic model will be introduced.

Advanced ADaM Dataset Development: Beyond the ADaMIG
Nancy Brucken, Mario Widel
Friday, September 27, 2019, 1:00 PM - 5:00 PM, Location: McCormick

This half-day course takes you beyond the examples in the ADaM Implementation Guide (ADaM IG), and shows you how to create analysis-ready datasets to meet more complex analysis requirements. Among the topics to be discussed are the addition of columns versus rows, approaches for handling multiple baseline definitions, creation of intermediate datasets while maintaining traceability back to SDTM, and avoidance of circular processing logic in ADSL. A working knowledge of basic ADaM structures and principles is expected.

SAS Data-Driven Development – Designing More Flexible, Reusable, Configurable, Maintainable Software
Troy Hughes
Friday, September 27, 2019, 1:00 PM - 5:00 PM, Location: Field

Students will receive a complimentary copy of the author’s 2019 book SAS Data-Driven Development: From Abstract Design to Dynamic Functionality, a $40 value! The course follows the book’s outline and teaches data-driven techniques in which software customization, configuration, business rules, data models, data cleaning/validation, report style, and other dynamic elements are maintained in external data structures – NOT in the underlying code. Data-driven development techniques allow software to adapt flexibly to various organizations, environments, and objectives. This design facilitates highly configurable (i.e., “codeless”) software whose functionality can be modified by changing only the underlying control tables, configuration files, parameters, user-specified options, and other control data.

In the first half of the course, participants will learn the basics of data-driven design and how dynamic elements can be identified within “code-driven” software and transformed into external data structures (control data):

Compare data-driven software design with functionally equivalent code-driven design, exploring the strengths and weaknesses of these contrasting methods.
Identify dynamic elements within software and learn the benefits of extracting these elements from code so they can be controlled remotely.
Create and read various file types that contain dynamic data elements, including batch files, configuration files, control files/tables, decision tables, business rule repositories, hierarchical taxonomies, and other data models.
Create and read various control data file formats, such as Excel spreadsheets, SAS data sets, XML files, CSS files, custom-formatted text files, and directory/folder contents.

In the second half of the course, participants will use data-driven methods to solve real-world problems more efficiently and effectively, with all examples demonstrated in SAS:

Learn SAS-specific components that support data-driven development, including the CALL EXECUTE statement, CNTLIN statement in PROC FORMAT, SYSPARM option, SAS dictionary tables, CSSSTYLE option in PROC REPORT, and SYMGET and SYMPUT functions.
Write batch files that parameterize dynamic elements to initiate and execute software using customized user specifications.
Clean, standardize, and categorize data using dynamic data formats and dynamic data models.
Create quality control except ion reports that use dynamic data dictionaries and data models to identify erroneous data.
Transform data using dynamic business rules and conditional logic maintained outside of software.
Create control tables that validate program/process success, indicate program/process failure, and which can be used as input by subsequent programs/processes to ensure that prerequisite steps completed successfully.
Customize the style (e.g., format, font, color scheme, graphics, etc.) and content of reports, graphs, and other data products through configuration files and dynamic style sheets

Custom Excel Spreadsheets Using PROC REPORT and the ODS Excel Destination
Kirk Lafler
Friday, September 27, 2019, 1:00 PM - 5:00 PM, Location: Wright

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.

Logistic Regression for Ordinal and Multinomial Data
Bruce Lund
Friday, September 27, 2019, 1:00 PM - 5:00 PM, Location: Burnham

This class introduces the topics of logistic regression for ordinal and multinomial data. The focus of the class includes “light” theory, supported by simulations, as well as practical suggestions for understanding and developing the models. These models are implemented using SAS® procedures LOGISTIC and HPLOGISTIC. For the ordinal model the target involves more than two levels and these levels are ordered. The focus is on the cumulative logit model (cum logit), including partial proportional odds. The conceptual basis of cum logit is presented and then practical suggestions are given for screening, binning, transforming of nominal, ordinal, discrete, and continuous predictors, oversampling for rare events, and predictor variable selection methods. Measures of fit and predictive accuracy are discussed. For the multinomial model the target involves more than two levels that are nominal (sometimes called a polytomous target). LOGISTIC and HPLOGISTIC fit this model. The approach of Begg and Gray (1984, Biometrika) for fitting the multinomial model by multiple binary logistic models is discussed. Finally, the generalization of the multinomial model to the discrete choice model is introduced. The discrete choice model allows for an interaction of target levels (choices) with values of predictors. In this connection, PROC MDC is presented.

Regression Expression! 24 Regression Methods in SAS: Part 1
David Corliss
Saturday, September 28, 2019, 8:00 AM - 12:00 PM, Location: Burnham

With so many regression procedures available for different situations, it can be difficult to know the breadth of available methods and how to select the ones to apply to a given problem. This course offers an overview of 24 regression-based methods. A decision flowchart is provided to assist in selecting the most useful regression procedures for a given context. The course is practical and example-driven, emphasizing which procedures to consider and how to apply them in real situations. A quick introduction to each method is followed by examples, with a discussion of use cases, options in the SAS procedures, and producing graphical output. The course begins with a basic overview of linear regression, progressing to more advanced techniques. Course modules include basic regression, procedures for specific data issues and needs (e.g., robust regression for outliers), special model types (e.g., quantile regression), logistic regression methods, and mixed, non-linear, and non-parametric SAS procedures. This course will help discern which statistical methods should be considered in a given situation and provide details with source code and examples for using specific procedures.

Building High-Impact Dashboards Using SAS® Base Software
Kirk Lafler, Josh Horstman
Saturday, September 28, 2019, 8:00 AM - 12:00 PM, Location: Field

Organizations around the world develop static and interactive reports, spreadsheets and dashboards for the purpose of displaying the current status of “point-in-time” data, charts, tables, reports, statistics, scorecards, metrics and key performance indicators. Effectively designed dashboards, along with the code behind them, involves the extraction of data from a variety of sources, the performance of a series of data cleaning steps, restructuring and reformatting data, and the production of charts, tables and reports with the purpose of highlighting important information, numbers, tables, statistics, metrics, performance information and other essential content on a single screen.

This popular half-day course explores the best practice programming techniques to build static and interactive drill-down dashboards (containing hyperlinks) using Base-SAS® software to drive awareness and understanding of summary and detail results. Attendees learn how to create high-impact dashboards with a purpose not in weeks or months, but in hours, using the DATA step; PROC FORMAT; PROC PRINT; PROC REPORT; PROC MEANS; PROC SQL; Output Delivery System (ODS); the macro language; Statistical Graphic procedures: PROC SGPLOT, PROC SGSCATTER, PROC SGPANEL, and PROC SGRENDER; Graphics Template Language (GTL); and PROC TEMPLATE.

Getting Started with PROC REPORT: Understanding the Building Blocks
Richann Watson
Saturday, September 28, 2019, 8:00 AM - 12:00 PM, Location: McCormick

Although PROC REPORT has been available since Version 6.07, the procedure is generally underutilized. One reason is that the syntax of the procedure is unique with the SAS System. Learning the basic structure in an organized way allows the programmer to easily transition from simple to increasingly more complex tables.

This Seminar will show how PROC REPORT works and thinks through a series of increasingly more complex examples. Examples will include:

An introduction to the basic syntax of the PROC step
Introduction to the COLMN, DEFINE, COMPUTE, BREAK, and RBREAK statements
The demonstration of addition of text to headers and value descriptions
The use of the DEFINE statement to form groups and columns
The generation of breaks before and after groups
The generation of breaks before and after the report
Use of Aliases

Regression Expression! 24 Regression Methods in SAS: Part 2
David Corliss
Saturday, September 28, 2019, 1:00 PM - 5:00 PM, Location: Burnham

With so many regression procedures available for different situations, it can be difficult to know the breadth of available methods and how to select the ones to apply to a given problem. This course offers an overview of 24 regression-based methods. A decision flowchart is provided to assist in selecting the most useful regression procedures for a given context. The course is practical and example-driven, emphasizing which procedures to consider and how to apply them in real situations. A quick introduction to each method is followed by examples, with a discussion of use cases, options in the SAS procedures, and producing graphical output. The course begins with a basic overview of linear regression, progressing to more advanced techniques. Course modules include basic regression, procedures for specific data issues and needs (e.g., robust regression for outliers), special model types (e.g., quantile regression), logistic regression methods, and mixed, non-linear, and non-parametric SAS procedures. This course will help discern which statistical methods should be considered in a given situation and provide details with source code and examples for using specific procedures.

Advanced SAS Macro Language Techniques for Building Dynamic Programs
Josh Horstman
Saturday, September 28, 2019, 1:00 PM - 5:00 PM, Location: Field

This seminar shows you how to take advantage of SAS Macro Language capabilities that enable you to write dynamic programs and applications. By mastering the concepts and techniques presented in this class your programs will become free of hard-coded data dependencies, thus eliminating the need to re-write the code every time a data set name, variable name, or other data attribute changes. Topics will include how to build and process macro variable lists, using the macro language to control the data environment, using control files, working with datasets and libraries in the macro language, accessing the SAS data dictionaries, and other miscellaneous macro topics that will help you create dynamic code.

Powerful PROC SQL Programming Techniques for SAS® Users and Programmers
Kirk Lafler
Saturday, September 28, 2019, 1:00 PM - 5:00 PM, Location: Wright

Structured Query Language (SQL) is a universal language used in data science, data analytics, statistics, data management, and other disciplines to access, transform, manipulate and output data stored in SAS data sets, relational databases and tables. Based on Kirk’s new PROC SQL: Beyond the Basics Using SAS®, Third Edition book, this half-day course presents core concepts and techniques to use PROC SQL as a programming and database language.

Attendees learn how to construct powerful and scalable queries; define, access, and manipulate data from one or more tables using PROC SQL; subset, order and group data; summarize data down rows and across columns using summary functions; join two or more tables using conventional (equi-joins) and unconventional (left, right and full outer join) methods; apply effective fuzzy matching programming techniques when a table’s key(s) are inconsistent or less than reliable; use the SQL-macro interface to create single-value (or aggregate) and value-list (array) macro variables; construct real-world queries including nearest neighbor processing; first, last and between By-group processing; produce customized output using Output Delivery System (ODS); construct powerful and scalable indexes to dynamically access rows of data; and query performance considerations.

Advanced PROC REPORT: Understanding the Compute Block and the Report Process
Richann Watson
Saturday, September 28, 2019, 1:00 PM - 5:00 PM, Location: McCormick

One of the unique features of the REPORT procedure is the Compute Block. This PROC step tool allows the use of most DATA step statements, logic, and functions. Through the use of the compute block you can modify existing columns, create new columns, write text, and more!

As is so often the case, this power and flexibility comes at a price. The compute block can be complicated. There are a number of column identification and timing issues that can confound the PROC REPORT user. Of course, to make matters even more interesting, there can be multiple compute blocks that can interact with each other and that can execute for different portions of the report table.

Manipulating Data with DO Loops and Arrays
Ben Cochran
Sunday, September 29, 2019, 8:00 AM - 12:00 PM, Location: Wright

This one day workshop explores the area of data manipulation and shows you how to accomplish this through using arrays and DO Loops within the SAS DATA step. The course begins with a section on DO Loops and explores many different DO Loop structures. Many examples are used to illustrate how to create data using DO Loops. Many examples show how to incorporate SAS functions into the DO Loop syntax. You may need a DO Loop that executes for a fixed number of cycles, or a DO Loop that executes until a certain condition is met. The section on DO Loops concludes with a look at Table Lookup operations.

The section on Arrays covers many different examples. After examining the syntax of the ARRAY statement, a series of examples on doing calculations, data conversions, and transposing SAS datasets is shown. Next, doing Table Lookup operations with SAS Arrays is discussed. This section concludes with a look at Multidimensional arrays and special functions that can make writing Array applications a little more elegant.

ODS Graphics I: Creating Quick and Easy Graphs with the Statistical Graphics (SG) Procedures
Josh Horstman
Sunday, September 29, 2019, 8:00 AM - 12:00 PM, Location: McCormick

The ODS Statistical Graphics (SG) Procedures represent a complete paradigm shift for the creation of high-quality graphics using the SAS system. Legacy SAS/GRAPH functions produce crude graphics that frequently do not meet today’s standards of presentation. While customization is possible, it can require extensive coding and several tricks to achieve desirable results. With the introduction of the SG procedures, all of that changed. This course will provide an overview of the major procedures such as SGPLOT, SGPANEL, and SGSCATTER as well as related statements and common options using numerous examples. Upon completion of the course, students will have the tools they need to start producing high-quality graphics and performing basic customization using the options available.

Macros for the Smart Programmer
Stephanie Thompson
Sunday, September 29, 2019, 8:00 AM - 12:00 PM, Location: Field

Why do smart programmers use macros? The top reasons are to make your code more flexible, dynamic, and less error prone. This workshop will highlight all of these areas with practical examples from both industry and higher education. There is so much you can do with the macro language and this workshop will provide you with lots of ways to use macro variables and macros in your programs. Learn about the automatic macro variables generated by your SAS session and how these can be used. There are some esoteric qualities of macros, but this workshop will focus on how to use them in real life. Various ways of creating macro variables will be covered, the foundations of macro code, and generating both static and dynamic iterative loops are just some of the areas that will be covered. Learn how macros can make your life as a programmer much easier.

Statistics 101: Introduction to Statistical Principles and Quantitative Analytics using SAS/STAT®
Michael Wilson
Sunday, September 29, 2019, 8:00 AM - 12:00 PM, Location: Ogden

Statistical Principles and Quantitative Analytics are investigative tools to extract meaningful information from data reliably and to guide smarter decisions. SAS/STAT has a rich, successful history of making those tools readily available and allowing for rapid customization. In this course, implementation of procedure-based tools using SAS/STAT will be introduced. Understanding fundamental concepts will be emphasized over mathematical derivation and formulae. The material in this course is a prerequisite to many statistical courses. At the conclusion of the course, participants will be able to communicate with statisticians more effectively, better clarify specific report requirements and have an improved understanding of statistical material in multi-disciplinary discussions and reports.

Modern Regression Techniques
Peter Flom
Sunday, September 29, 2019, 1:00 PM - 5:00 PM, Location: Ogden

The analytical problems that we encounter often violate the assumptions of the general linear model (linear regression and ANOVA). Modern modeling techniques have been created to overcome these violations and provide better results. SAS has created PROCs so that we can easily implement these modern techniques. This half-day course will teach you how to use these SAS PROCs to implement Quantile regression, Robust regression, Cubic splines and other forms of splines, Multivariate adaptive regression splines (MARS), and Regression trees so that you will create better insights for your organization.

What Can PROC SQL Do for You?
Stephanie Thompson
Sunday, September 29, 2019, 1:00 PM - 5:00 PM, Location: Wright

PROC SQL can be a powerful tool in your programmer’s toolkit. There are things that can be done easily using SQL that can be a little more challenging with other PROCS. This workshop will walk you through the basics of PROC SQL as well as highlight the differences to other approaches in SAS. Syntax, creating tables, types of joins, generating new variables, and using summary functions will be covered. The workshop will also go over some of the more advanced features of SQL such as using the HAVING clause and sub-queries. A discussion of the benefits of using PROC SQL to access external databases and the benefits of SQL pushback will be presented as well.

ODS Graphics II: Mastering Custom Graphs with Graph Template Language (GTL)
Richann Watson
Sunday, September 29, 2019, 1:00 PM - 5:00 PM, Location: McCormick

Anyone who has produced a graph using ODS Graphics has unknowingly used the Graph Template Language (GTL). ODS graphics produced by SAS® procedures such as the Statistical Graphics (SG) procedures actually rely on pre-defined templates built with GTL. GTL generates graphs using a template definition that provides extensive control over its format and appearance. Although most of the graphs produced within a procedure are adequate for most situations, they sometimes lack those one or two extra features you need to really make your graphs stand out and impress your clients or customers. GTL, as an extension of ODS Graphics, allows users much greater flexibility in creating specialized graphs. In this class, you'll learn how to use GTL to create complex, highly customized graphics that you could only dream about before. We'll cover the different types of layouts provided by GTL as well as various types of plots. The focus of the course will be on three specific layouts (i.e., OVERLAY, GRIDDED and LATTICE) and the more common types of plots (e.g., BARCHART, BLOCKPLOT, BOXPLOT, HIGHLOWPLOT, SCATTERPLOT and SERIESPLOT). Through the use of detailed examples, you will learn how to build your own template to make customized graphs and how to create that one highly desired, unique graph that at first glance seems impossible.

Express Yourself with Python in SAS
Charu Shankar
Sunday, September 29, 2019, 1:00 PM - 5:00 PM, Location: Field

With the entry of several open source languages, users feel the need to learn them and understand the differences and commonalities between them. Come learn how to express your data needs by writing python panda. Python is completely different from SAS. Learn how Python stacks up with SAS code, and do a compare and contrast. Learn how you can write native python code and submit it in your SAS session. All necessary software links will be provided by the instructor for this informative education seminar

Instructor Biographies

Nancy Brucken

Nancy Brucken has used SAS in the pharmaceutical industry for over 25 years. She has been a member of the ADaM team since 2011, and has worked on the ADaMIG v1.1, v1.2, OCCDS v1.0 and Traceability sub-teams, and currently co-leads the ADQRS sub-team.

Ben Cochran

After more than 11 years with SAS Institute in the Professional Services (as an Instructor) and Marketing Departments (as Marketing Manager for the SAS/EIS product), Ben Cochran left to start his own consulting and SAS Training business in the fall of 1996 – The Bedford Group. As an affiliate member of SAS Institute’s Alliance Partner Program, Ben has been involved in many teaching and consulting projects over the last 20+ years. Ben has authored and presented several papers at SUGI, SGF, and regional user groups on a variety of topics since 1988.

David Corliss

Dr. David J Corliss is a statistical astrophysicist specializing in the dynamics of evolving stellar and cosmic populations. A SAS user since1995, with extensive work in statistical methods, time series analysis, reporting and visualization, operations research, big data methods, and analytic platform design. He presents regularly at local and national SAS events and other conferences. He is active in the American Statistical Association, writing a monthly column in Amstat News on Data for Good and serving on the steering committee of the Conference on Statistical Practice. Dr. Corliss is the Founder and Director of Peace-Work, an all-volunteer Data For Good collaboration of statisticians and data scientists providing analytic support for charitable groups and applying statistical methods in issue-driven advocacy for richer lives, stronger communities, and a better world.

Peter Flom

Peter Flom is an independent statistical consultant working with graduate students and researchers in the social, medical and behavioral sciences. He has been using SAS for over 20 years and has given talks at SGF and many local and regional groups. He is also working on a book with the same subject matter as this course.

Josh Horstman

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 at SAS Global Forum and various regional and local SAS users group. Josh holds a bachelor's degree in mathematics and computer science, and a master's degree in statistics from Colorado State University.

Troy Hughes

Troy has more than 20 years of experience leading SAS teams and projects in support of federal, state, and local government initiatives. Since 2013, he has given more than 90 presentations, trainings, and hands-on workshops at SAS conferences, including at SAS Global Forum, SAS Analytics Experience, WUSS, SCSUG, SESUG, MWSUG, and PharmaSUG. Additionally, he has authored two books that model design and development best practices: - SAS Data Analytic Development: Dimensions of Software Quality (2016) - SAS Data-Driven Development: From Abstract Design to Dynamic Functionality (2019) Troy has an MBA in information systems management and numerous certifications including SAS Base, SAS Advanced, SAS Clinical Trials, PMP, PMI-RMP, PMI-PBA, PMI-ACP, CISSP, CSSLP, ITIL, CSM, CSD, CSPO, CSP-SM, and CSP-PO. He is a US Navy veteran with two tours of duty in Afghanistan.

Kirk Lafler

Kirk Paul Lafler is an entrepreneur and founder at Software Intelligence Corporation, and has used SAS software since 1979 as a consultant, application developer, programmer, SAS solutions provider, data analyst, data manager, infrastructure specialist, performance tuner, educator and author. As a SAS Certified professional, mentor, and educator at Software Intelligence Corporation, and an advisor and adjunct professor at the University of California San Diego Extension, Kirk has taught SAS courses, seminars, workshops, and webinars to thousands of users around the world. Kirk is also the author of several books including PROC SQL: Beyond the Basics Using SAS, Third Edition (SAS Press. 2019) along with hundreds of papers and articles on a variety of SAS topics; has been selected as an Invited speaker, educator, keynote and section leader at SAS conferences and meetings worldwide; and is the recipient of 25 “Best” contributed paper, hands-on workshop (HOW), and poster awards.

Bruce Lund

Bruce Lund is an independent consultant who specializes in predictive modeling. For the prior 15 years he was a consultant for OneMagnify of Detroit. Before OneMagnify, he was the customer database manager at Ford Motor Company and a mathematics professor at University of New Brunswick, Canada. He has a mathematics PhD from Stanford University. Bruce Lund has presented at SAS Global Forum, SAS AnalyticsX, ASA CSP, and frequently at MWSUG. He has used SAS for over 30 years.

Charu Shankar

SAS Senior Technical Training Specialist, Charu Shankar teaches by engaging with logic, visuals and analogies to spark critical thinking. She interviews clients to recommend the right SAS training. She is a frequent blogger for the SAS Training Post. When she’s not teaching technology, she is passionate about helping people come alive with yoga and is a food blogger. Charu has presented at over 100 SAS international user group conferences on topics related to SAS programming, SQL , DS2 programming, big data and Hadoop, tips and tricks with coding, new features of SAS and SAS Enterprise Guide.

Stephanie Thompson

Stephanie Thompson has over twenty years of experience in applying statistical and modeling techniques to solve business problems in various commercial and academic environments. Strong understanding of data structures, a variety of analytical tools, and operating environments. Views problems (opportunities?) in a broad context by examining the interrelations between issues and the local and broader operational framework. Demonstrated skill at effectively communicating and working across multiple functional areas and at all organizational levels. Stephanie has made dozens of presentations at local, regional, and international meetings and conferences to technical and non-technical audiences.

Richann Watson

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.

Mario Widel

Mario Widel is an independent contractor. He has been involved in CDISC related activities since 2007. In his current role, Mario focuses on process development for submission data and documentation. He is a member of the ADaM team, a CDISC authorized SDTM and ADaM instructor and has presented at numerous conferences including PharmaSUG, JSM, SAS Global Forum and PhUSE.

Michael G. Wilson

Michael G. Wilson has been a practicing statistician using SAS/STAT for 30 years. In addition, he has been a part-time faculty and adjunct faculty member for the past 12 years teaching statistics at the university, advanced graduate and medical school levels. Michael has co-authored over 50 peer-reviewed research journal articles. Currently, he is an independent biostatistician and co-investigator of NIH and VA studies.