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Common Statistical Methods for Clinical Research with SAS Examples, Second Edition
 
 
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Common Statistical Methods for Clinical Research with SAS Examples, Second Edition [Paperback]

Glenn A. Walker (Author)
4.4 out of 5 stars  See all reviews (7 customer reviews)


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Book Description

1590470400 978-1590470404 July 15, 2002 2nd
Common Statistical Methods for Clinical Research with SAS Examples, Second Edition, written by Glenn Walker, provides clinical researchers with an invaluable aid for understanding the statistical methods cited most frequently in clinical protocols, statistical analysis plans, clinical and statistical reports, and medical journals. The text is written in a way that takes the non-statistician through each test using examples, yet substantive details are presented that benefit even the most experienced data analyst. Introductory chapters provide elementary statistical concepts as applied to clinical trials and an overview of statistical inference, including discussions about power, calculating sample size, p-values, and the logic behind hypothesis testing. The statistical methods discussed here represent a composite of methods most commonly used in the analysis of clinical research data. Numerous examples taken from clinical research show how to calculate statistical data both manually and using SAS. This revised edition includes sections about crossover designs and multiple comparison methods, a discussion of interim analyses, 50% more examples, and reader exercises. Extensions of methods previously presented only in their most elementary form are shown in new examples.


Editorial Reviews

Review

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.

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

About the Author

Glenn A. Walker has been providing statistical consulting services to the biopharmaceutical industry since 1977. He received his Ph.D. in statistics from the University of Florida where, as a graduate student, he taught courses in statistics and how to use SAS software. He has worked as a consultant to numerous pharmaceutical and biotechnology companies in study design, data analysis, and statistical programming in the field of clinical trials. In this book, Glenn draws on his extensive experience with the statistical handling of data from various types of medical conditions and treatments to illustrate commonly used statistical methods.

Product Details

  • Paperback: 488 pages
  • Publisher: SAS Publishing; 2nd edition (July 15, 2002)
  • Language: English
  • ISBN-10: 1590470400
  • ISBN-13: 978-1590470404
  • Product Dimensions: 11 x 8.2 x 1.2 inches
  • Shipping Weight: 2.4 pounds
  • Average Customer Review: 4.4 out of 5 stars  See all reviews (7 customer reviews)
  • Amazon Best Sellers Rank: #646,024 in Books (See Top 100 in Books)

More About the Author

Glenn Walker received his Ph.D. in statistics from the University of Florida in 1977. As a graduate student, he was introduced to the consulting experience while working on research projects for Shands Hospital at UF. He also became self-taught in SAS, a new statistical software package at the time, and taught SAS to undergraduate students. He later worked for Abbott Laboratories in Chicago for many years before moving to California as an independent statistical consultant for the pharmaceutical industry and others conducting clinical trials. In 25 years as a consultant, he worked with a variety of large and small pharmaceutical and biotechnology companies and countless, diverse projects giving him a vast portfolio of experience upon which to draw as a basis for his book, "Common Statistical Methods for Clinical Research with SAS Examples". Now retired, Glenn continues to update his popular book with current material, which is in its 3rd Edition.

 

Customer Reviews

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27 of 27 people found the following review helpful:
5.0 out of 5 stars great introduction to biostatistics in context of SAS implementation, March 1, 2008
This review is from: Common Statistical Methods for Clinical Research with SAS Examples, Second Edition (Paperback)
This book covers all the SAS procedures applicable in clinical trials. It provides excellent examples to illustrate the methodology and the precise way to produce the results in SAS. It also gives the reader a very clear and detailed presentation of the output. It is so good that when we were validating Version 9 of SAS we took some examples from Walker's book that we tried to replicate. We had to keep in mind some minor differences between Version 9 and Verson 6 which is th basis for Walker's examples.
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7 of 7 people found the following review helpful:
5.0 out of 5 stars One of a kind, March 15, 2003
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This review is from: Common Statistical Methods for Clinical Research with SAS Examples, Second Edition (Paperback)
This book is very instructive for those interested in the pharmaceutical field or might already be in, especially for those not having a statistics degree. The different tests are explained and tell you for what situations they can be applied to. Good examples with SAS code and sample data are provided. For most problems, manual calculations are shown before doing them in SAS. This book was not that easy to digest though. Multiple reading will make the material more clear.
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6 of 6 people found the following review helpful:
3.0 out of 5 stars decent book, January 7, 2004
This review is from: Common Statistical Methods for Clinical Research with SAS Examples, Second Edition (Paperback)
This book have a lot of examples with sas codes, outputs, and explanations of outputs, which is useful for practitioners. Recommended for practitioners, but not for serious statisticians who seek in-depth and accurate, a little more mathematical treatment of the topics instead of just explanations of sas codes/outputs.
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Inside This Book (learn more)
First Sentence:
In some ways, we are all born statisticians. Read the first page
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Corrected Total, Sum of Source, Mean Std Dev, R-Square Coeff Var Root, Estimate Error, Pillai's Trace, Value Prob, Hotelling-Lawley Trace, Central Limit Theorem, Roy's Greatest Root, Frequency Row Pct, Cancer Types, Examples Example, Statistic Value, Value Num, Multivariate Approach, Res Log Likelihood, Test Chi-Square, Analysis of Covariance Example, Arthritic Discomfort Following Vaccine, Contingency Coefficient, Contrast Variable, Logistic Regression Example, Nonzero Correlation, Phi Coefficient
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