Richann Watson and Kriss Harris showcase their combined 40 years of hands-on SAS experience in this must-read tome. Clinical programmers and other professionals in the pharmaceutical or clinical trials industries will welcome the detailed explanations that explore criteria to consider when selecting and designing stunning visual output—while those outside of these industries will find the examples clear, concise, and generalizable across organizations and objectives.
The authors expertly demonstrate various statistical graphics (SG) procedures, as well as advanced topics such as Graph Template Language (GTL), which can be used to extend, customize, and automate graphics output. Examples begin with realistic scenarios that depict the business need for data visualization, followed by annotated SAS code (also available on GitHub), and more than 80 color graphs and dozens of customized tables. Readers will gain not only graphing basics, but the ability to produce print-ready output for inclusion in peer-reviewed journal articles and other publications.
Whether you are searching for a four-way Venn diagram, a dual-axis series plot, or best practices on how to design and automatically position trendlines, statistics, labels, and iconography—SAS Graphics for Clinical Trials by Example will equip you to better understand, visualize, and communicate your most essential data.
Troy Martin Hughes
For newcomers to statistical graphics, coding, especially with Graphic Template Language (GTL), can be daunting. Kriss Harris and RichAnn Watson’s book on SAS Graphics for Clinical Trials by Example is a godsend! It provides useful examples on how to customize commonly used graphs in the pharmaceutical and biotech industries and more. These examples come with useful SAS code, annotated with clear and concise explanations; users can have a clear understanding and modify this sample code to suit their needs.
Because one of the authors, Kriss Harris is from the United Kingdom, there is an international flavor! There are examples for graphical representation of adverse events, which are not commonly included in Clinical Study Reports in the United States, but are used more often in Europe.
Armed with this book, programmers can approach statistical graphics with confidence! This book is a MUST-HAVE.
Whichever version of this book you plan to buy, hardcopy or online, you’ll get your money’s worth. The book is a highly concentrated exposition of how graphics can be used to illuminate the meaning of clinical trials data. As such, it must be sipped, not gulped. The authors have put a tremendous amount of thought into the content. Every part of the book is valuable and must be digested slowly and carefully.
Each chapter stands alone and references a specific variety of clinical data. It shows how to produce analytical graphs related to the collected data. One chapter illustrates how to do frequently required graphic analyses of adverse events. Another chapter looks at time-to-event. Another chapter shows tumor response graphs, There are more. In each case, the book shows the precise details about how to present and interpret medical information visually.
What’s noteworthy is that the authors understand the “business” basis for producing graphs, i.e., disease-related medical information needs. SAS techniques and domain expertise are combined. Other people working on clinical trials will encounter similar medical analysis needs time and again, and the book’s usefulness to them is guaranteed.
Dr. Jim Sattler, President
Satmari Software Systems, Inc.
In addition to the examples, the sample code and the illustrations to the options are very useful so that users can choose the template options that fit the data visualization purpose best. I would recommend this book to all programmers working on clinical trials.
Eason Yang (Yi Yang)
The authors do a fantastic job of meeting clinical programmers where they are and offering the tools they need to solve their particular problem. Whether you have a specific project in mind, or just want to learn more about how to improve your clinical graphs in SAS, this book is a must-have!
Deanna (DeDe) Naomi Schreiber-Gregory
Co-owner, Operations and Finance
Independent Consultant - Statistics & Data Management