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Science/Engineering Common Statistical Methods for Clinical Research: With SAS Examples

Posted on 2010-03-15




Name:Science/Engineering Common Statistical Methods for Clinical Research: With SAS Examples
ASIN/ISBN:1590470400
Language:English
File size:20 Mb
Publisher: SAS Publishing
Publish Date: Jul 2002
ISBN: 1590470400
Pages: 488 pages
File Type: PDF
File Size: 20 MB
   Science/Engineering Common Statistical Methods for Clinical Research: With SAS Examples

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Glenn A. Walker, "Common Statistical Methods for Clinical Research: With SAS Examples"

Review

Are you tasked to use statistical methodology without sufficient statistical training? As part of your work do you interface with statisticians who use jargon that only slightly resembles English? Do you need to perform statistical analyses and present the results of statistical tests using SAS without a clear understanding of the procedures or their output? This book is for you. Although filled with examples relating to the clinical industry, this book provides a much broader reach and is appropriate for any setting that applies statistical methodology. With the second edition of Common Statistical Methods for Clinical Research with SAS Examples Glenn Walker has added almost 100 pages of new information. More importantly he has enhanced its readability for analysts and non-statisticians. The book's organization flows well not only from chapter to chapter but also within each chapter. --Art Carpenter, California Occidental Consultants

The novice as well as seasoned statisticians will benefit from this insightful journey into statistics and the use of SAS®. -- Stephan Ogenstad, Ph.D., Senior Director, Biometrics Vertex Pharmaceuticals, Inc.

This book is an extension and improvement to the excellent first edition appearing in 1996. Each chapter has an introduction covering the specific method and gives examples of where the method is used. The introduction is followed by a synopsis presenting the necessary and significant information for the reader to get a good understanding of the statistical method. Excellent examples are given, including illustrations and followed by the SAS code for the example. Detailed annotations make the SAS output easy to understand. The book also gives numerous extensions for the methods. Dr. Walker has certainly used his many years of consulting experience, his teaching experience with the University of Florida, and his understanding of SAS to produce an even better book, equally understandable and helpful to the novice as well as the seasoned statistician. Each will benefit from this insightful journey into statistics and the use of SAS, whether as a teaching tool or a refresher. I can recommend this book wholeheartedly. --Stephan Ogenstad, Ph.D., Senior Director, Biometrics Vertex Pharmaceuticals, Inc.

This book is filled with examples relating to the clinical industry. It is appropriate for any setting applying statistical methodology. -- Art Carpenter, California Occidental Consultants

Product Description

Clinical researchers, with or without a statistical background, will find this book an invaluable aid in understanding the statistical methods cited most frequently in clinical protocols, statistical analysis plans, clinical and statistical reports, and medical journals. Written in a manner which leads the nonstatistician through each test by example, substantive details are presented which will benefit even the experienced data analysts. Introductory chapters provide elementary statistical concepts as applied to clinical trials and an overview of statistical inference, including discussions of power, sample size calculations, p-values and the logic behind hypothesis testing. Numerous examples from clinical research are worked through both manually and using SAS. Methods presented include t-tests, analysis of variance, repeated measures ANOVA, linear regression, analysis of covariance, non-parametric tests, binomial tests, chi-square test, Fisher's exact test, McNemar's test, Cochran-Mantel-Haenszel test, logistic regression, log-rank test, and Cox proportional hazards model.

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