Chen D.-G., Peace K.E., Zhang P. Clinical Trial Data Analysis using R and SAS

Boca Raton: CRC Press, 2017. — 391 p.With the exception of two chapters, our first book: “Clinical Trial Methodology” (Peace and Chen (2010)) contained no statistical analysis software code for the analysis results presented therein. In this book we provide a thorough presentation of biostatistical analyses of clinical trial data with detailed step-by-step illustrations on their implementation using R. In each chapter, examples of clinical trials based on the authors’ actual experience in many areas of clinical drug development are presented. After understanding the application, various biostatistical methods appropriate for analyzing data from the clinical trials are identified. Then analysis code is developed using appropriate R packages and functions to analyze the data. Analysis code development and results are presented in a stepwise fashion. This stepwise approach should enable readers to follow the logic and gain an understanding of the analysis methods and the R implementation so that they may use R to analyze their own clinical trial data.
Based on their experience in biostatistical research and working in clinical development, the authors understand that there are gaps between developed statistical methods and applications of statistical methods by students and practitioners. This book is intended to fill this gap by illustrating the implementation of statistical methods using R applied to real clinical trial data following a step-by-step presentation style.
With this style, the book is suitable as a text for a course in clinical trial data analysis at the graduate level (Master’s or Doctorate’s), particularly for students seeking degrees in statistics or biostatistics. In addition, the book should be a valuable reference for self-study and a learning tool for clinical trial practitioners and biostatisticians in public health, medical research universities, governmental agencies and the pharmaceutical industry, particularly those with little or no experience in using R.
Since the publication of the first edition of this book in 2011, we have received extensive compliments on how well it was structured for use by clinical trial statisticians and analysts in analyzing their own clinical trial data following the detailed step-by-step illustrations using R. We have also received suggestions and comments for further improvement among which is to add SAS to the new edition. A feature of this second edition is to also illustrate data analyses using the SAS system. Therefore, in this second edition, we have incorporated all suggestions and comments from enthusiastic readers and corrected all errors and typos in addition to including SAS programs for data analysis. The SAS programs appear in the appendix of each chapter corresponding to the sections where analyses using R were performed.