In Analysis of Clinical Trials Using SAS: A Practical Guide, Alex Dmitrienko, Geert Molenberghs, Christy Chuang-Stein, and Walter Offen bridge 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 the 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 important statistical problems encountered in clinical trials, including analysis of stratified data, incomplete data, multiple inferences, issues arising in safety and efficacy monitoring, and 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.
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"This book covers many important topics applied biostatisticians encounter every day. It will be a big addition to the existing literature on the analysis of clinical trials using SAS, and I expect this book is much needed. The feature I like most about Analysis of Clinical Trials Using SAS: A Practical Guide is that it not only gives comprehensive reviews and summaries of developments on several very important topics, but also provides practical guide on how the methodologies can be implemented in the SAS environment. I strongly agree with the authors that the experienced biostatisticians who are involved in the design and analysis of clinical trials will find the book very helpful, as will graduate students specializing in biostatistics."
In Analysis of Clinical Trials Using SAS: A Practical Guide, Alex Dmitrienko, Geert Molenberghs, Christy Chuang-Stein, and Walter Offen bridge 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 the 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 important statistical problems encountered in clinical trials, including analysis of stratified data, incomplete data, multiple inferences, issues arising in safety and efficacy monitoring, and 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.
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