SAS Programming in the Pharmaceutical Industry, Second Edition

  • 4h 21m
  • Jack Shostak
  • SAS Institute
  • 2014

This comprehensive resource provides on-the-job training for statistical programmers who use SAS in the pharmaceutical industry.

This one-stop resource offers a complete review of what entry- to intermediate-level statistical programmers need to know in order to help with the analysis and reporting of clinical trial data in the pharmaceutical industry.

SAS Programming in the Pharmaceutical Industry, Second Edition begins with an introduction to the pharmaceutical industry and the work environment of a statistical programmer. Then it gives a chronological explanation of what you need to know to do the job. It includes information on importing and massaging data into analysis data sets, producing clinical trial output, and exporting data. This edition has been updated for SAS 9.4, and it features new graphics as well as all new examples using CDISC SDTM or ADaM model data structures.

Whether you're a novice seeking an introduction to SAS programming in the pharmaceutical industry or a junior-level programmer exploring new approaches to problem solving, this real-world reference guide offers a wealth of practical suggestions to help you sharpen your skills.

About the Author

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.

In this Book

  • Environment and Guiding Principles
  • Preparing and Classifying Clinical Trial Data
  • Importing Data
  • Transforming Data and Creating Analysis Data Sets
  • Creating Tables and Listings
  • Creating Clinical Trial Graphs
  • Performing Common Analyses and Obtaining Statistics
  • Exporting Data
  • The Future of SAS Programming in Clinical Trials
  • Further Resources