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Analysis of Clinical Trials Using SAS

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Written by Dr. Alex Dmitrienko (Eli Lilly and Company), Prof. Geert Molenberghs (Hasselt University), Dr. Christy Chuang-Stein (Pfizer) and Dr. Walter Offen (Eli Lilly and Company). The book is available on Amazon's web site.

Description

This comprehensive guide bridges the gap between modern statistical methodology and real-world clinical trial applications. Step-by-step instructions illustrated with examples from actual trials and case studies serve to define a statistical method and its relevance in a clinical trials setting and to illustrate how to implement that method rapidly and efficiently using the power of SAS software. Topics reflect the International Conference on Harmonization (ICH) guidelines for the pharmaceutical industry and address the important statistical problems encountered in clinical trials, including analysis of stratified data, analysis of incomplete data, multiple inferences, issues arising in safety and efficacy monitoring, reference intervals for extreme safety and diagnostic measurements.

Clinical statisticians, research scientists, and graduate students in biostatistics will greatly benefit from the decades of clinical research experience compiled in this book. Numerous ready-to-use SAS macros and example code are included.

Praise from the experts

Peter H. Westfall, Professor of Statistics, Texas Tech University

This book will be very useful for statisticians who wish to learn the most current statistical methodologies in clinical trials. The authors make use of recent developments in SAS–including stratification, multiple imputation, mixed models, nonparametrics, and multiple comparisons procedures–to provide cutting-edge tools that are either difficult to find or unavailable in other software packages. Researchers in all fields who carry out comparative studies would do well to have the book on their bookshelves.

Gordon Lan, Senior Director, Biometrics and Clinical Informatics, Johnson and Johnson

This book provides an excellent overview of many statistical methods used in clinical trial design and data analysis. It is much more than a collection of SAS programs. The authors share their experience in examples and discussions that give an in-depth insight into many practical problems you may face in the real world.

Book outline

Chapter 1. Analysis of Stratified Data.

Chapter 2. Multiple Comparisons and Multiple Endpoints.

Chapter 3. Analysis of Safety and Diagnostic Data.

Chapter 4. Interim Data Monitoring.

Chapter 5. Analysis of Incomplete Data.