» Pharmaceutical Statistics Using SAS: A Practical Guide (SAS Press)

Pharmaceutical Statistics Using SAS: A Practical Guide (SAS Press) Reviews

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Summary: a must buy for biostatisticians doing clinical, pre-clinical or non-clinical pharmaceutical statistical research
Comment: ISBN: 978-1-59047-886-8 Pharmaceutical Statistics Using SAS: A Practical Guide.
I just received this book to review for the journal Technometrics. If you want to see a thorough professional review of all the chapters wait for the journal book reviews be me and others that will be forthcoming over the next couple of years. But if you just want to know now whether or not this book is for you read on.

This is a collection of chapters on application of modern statistical methods in the various phases of drug discovery and clinical research with an emphasis on clinical research but also with plenty of good material to satisfy the interest of those doing pre-clinical and non-clinical research. It contains state-of-the-art methodology and the chapters are written by the leading biostatisticians both in industry and academia. It includes an introductory chapter by Chuang-Stein and D'Agostino. The remaining 13 chapters contain specific applications with illustraions and solutions in SAS. This is great for biostatisticians in this industry who usually have SAS as their primary statistics package. But as pointed out by one of the expert reviewers. If you find this book in a bookstore read the first two pages which give you some of the reasons the experts think this is a greta buy. The reviews listed there are by Peter Westfall, Frank Shen, Byron Jones, Jose Pinheiro and Barry Davis.

The editors of the book are also leading experts and they have loaded the book with material on the various phases of drug development covering all the key topics. Many of the authors are also well-known for the contributions to biostatistics either in industry or academia or both.

I am so enthusiastic about this book that I have already recommended it to many of my friends in the pharmaceutical industry. Although the chapters include state-of-the-art research along with the commonly used procedures, the chapters are well-written and treated in an introductory way. So the book may be accessible to clinical researchers as well as statisticians as a great reference source. In addition to detailed SAS code to implement the methods the chapters also include extensive bibliographies for those wishing to learn the nitty gritty and better understand the theory behind the techniques.

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