Jack Shostak
Associate Director of Statistics, Duke Clinical Research Institute
Jack Shostak, Associate Director of Statistics, manages a group of statistical programmers at the Duke Clinical Research Institute. A SAS user since 1985, he is the author of SAS Programming in the Pharmaceutical Industry, and coauthor of Common Statistical Methods for Clinical Research with SAS Examples, Third Edition, as well as Implementing CDISC Using SAS: An End-to-End Guide. Shostak has published papers for the Pharmaceutical SAS Users Group (PharmaSUG) and the NorthEast SAS Users Group (NESUG), and he contributed a chapter, "Reporting and SAS Tool Selection," in the book Reporting from the Field. He is active in the Clinical Data Interchange Standards Consortium (CDISC) community, contributing to the development of Analysis Data Model (ADaM), and he serves as an ADaM trainer for CDISC. Shostak received an MBA from James Madison University and a BS in statistics from Virginia Polytechnic Institute and State University.
By This Author
Implementing CDISC Using SAS®: An End-to-End Guide, Revised Second Edition
By Chris Holland and Jack Shostak
Comprehensive guide on applying clinical research data and metadata to the CDISC standards. This edition reflects the 2017 FDA mandate for adherence to CDISC standards. Revised to add the latest C-Codes as well as update the make_define macro that accompanies this book in order to add the capability to handle C-Codes.
*Our books are also available in print and e-book formats
from your local bookstore or favorite online bookseller.
SAS® Programming in the Pharmaceutical Industry, Second Edition
By Jack Shostak
Discover tools available within Base SAS (including the macro language and PROC SQL), SAS/GRAPH, and SAS/STAT that can be used to resolve common issues in working with clinical trial data. Addresses importing and massaging data into analysis data sets, producing clinical trial output, and exporting data.
*Our books are also available in print and e-book formats
from your local bookstore or favorite online bookseller.
Common Statistical Methods for Clinical Research with SAS® Examples, Third Edition
By Glenn A. Walker and Jack Shostak
This new edition has been extensively updated to include the use of ODS graphics in numerous examples as well as a new emphasis on PROC MIXED. Straightforward and easy to use as either a text or a reference, the book is full of practical examples from clinical research to illustrate both statistical and SAS methodology. Each example is worked out completely, step by step, from the raw data.
*Our books are also available in print and e-book formats
from your local bookstore or favorite online bookseller.
Implementing CDISC Using SAS®: An End-to-End Guide, Second Edition
By Chris Holland and Jack Shostak
*Replaced by a revised edition Implementing CDISC Using SAS®: An End-to-End Guide, Revised Second Edition
Implementing CDISC Using SAS®: An End-to-End Guide
By Chris Holland and Jack Shostak
*Replaced by a revised edition, Implementing CDISC Using SAS®: An End-to-End Guide, Revised Second Edition
SAS® Programming in the Pharmaceutical Industry
Awards
2014-2015 Society for Technical Communication:
Award of Excellence: SAS® Programming in the Pharmaceutical Industry, Second Edition
Featured Authors
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Todd Case has been working in the pharmaceutical industry as a statistical programmer for over 20 years. He completed his MS in Epidemiology from Columbia University and has worked at Forest Laboratories (now Allergan), Genentech, Bristol-Myers Squibb, and Biogen. He currently works at Vertex Pharmaceuticals.
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Ron Klimberg, PhD, is a professor at the Haub School of Business at Saint Joseph's University in Philadelphia, PA.
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Robert N. Rodriguez retired from SAS in 2018 after serving as a senior director in research and development. Bob received a PhD in statistics from the University of North Carolina at Chapel Hill and was a research statistician at General Motors Research Laboratories before joining SAS.
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Terisa Roberts is a director and Global Solution lead for Risk Modeling and Decisioning at SAS. She has extensive experience in quantitative risk management, regulatory compliance, and model governance and validation. She has worked in financial services, telecommunications, government, energy, and retail sectors.