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Common Statistical Methods for Clinical Research with SAS Examples, Third Edition, by Glenn A. Walker, Jack Shostak
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Thoroughly updated edition of the popular introductory statistics book for clinical researchers. This new edition has been extensively updated to include the use of ODS graphics in numerous examples as well as a new emphasis on PROC MIXED.
- Sales Rank: #1536489 in eBooks
- Published on: 2010-02-15
- Released on: 2010-02-15
- Format: Kindle eBook
Review
"For anyone working as a statistician, SAS programmer, or clinical researcher who does pharmaceutical statistics using SAS this book is indispensable."
Michael R. Chernick, Ph.D.
Director of Biostatistical Services
Lankenau Institute for Medical Research
"This book is an excellent resource for all health care research with detailed information on common statistical methods and abundant SAS examples. From t-tests to logistic regression, this book covers it all. With the use of relevant examples and datasets, Walker and Shostak cover everything from data analysis to model fitting in an easy-to-read and easy-to-understand manner. The most comprehensive book on common statistical methods, Walker and Shostak's book is one of the books that I will use on a daily basis."
Kimberly Nguyen, M.S., M.P.H.
Epidemiologist
Connecticut Department of Public Health
�"Walker and Shostak offer a comprehensive introduction to fundamentals, concepts, and applications of statistics in clinical trials. Using data examples from drug development, sample SAS code is provided to help solve problems commonly found in clinical trials. Useful explanations of SAS code are given and common pitfalls are shown.
This book is a good reference for SAS programmers, clinicians, students, and professionals who want to learn SAS applications but may not have either clinical trials experience or statistical course work."
Debbi Kotlovker
Statistical Consultan
�
About the Author
Now retired, Glenn Walker worked for twenty-eight years as a statistician in clinical trials and health-related research. He has worked as an independent consultant for clinical researchers in the biotechnology and pharmaceutical industries, including numerous CROs. A SAS user since 1976, Glenn received his PhD in statistics from the University of Florida, where, as a graduate student, he taught courses in statistics and on how to use SAS software. Jack Shostak is the associate director of statistics for the Duke Clinical Research Institute, where he oversees a team of statistical programmers and serves as a CDISC resource. A SAS user since 1985, he is the author of SAS Programming in the Pharmaceutical Industry, also published by SAS Press. Jack received his MBA from James Madison University. He is active in the Pharmaceutical Industry SAS Users Group (PharmaSUG) and SAS Global Forum.
Most helpful customer reviews
14 of 14 people found the following review helpful.
The perfect place to start
By I Teach Typing
The 3rd edition of this book is as excellent as the first two. It covers the same core set of common analyses as the second edition but this one adds in more graphics, better coverage of repeated measures, it uses mixed effects models instead of older repeated measures ANOVA methods(don't worry if you don't know what that means), there is a bit about power calculations and throughout the book the code has been updated with modern syntax and new language features. The information on the new diagnostics associated with many of the old procedures is extremely valuable.
I highly recommend this for students or doctors who want to get their hands into the guts of SAS analysis code. What it lacks in statistical rigor and proofs it more than makes up for with easy to read instruction and well annotated code examples.
*** My review of the 2nd edition ***
I have been teaching biostatistics and data management for many years and on the first day of the year I always tell incoming MDs, masters and PhD level students who are not mathematicians to go out immediately and get this book. When they graduate, they frequently spontaneously tell me that it was excellent advice and they tell me the book "saved" them either in class or on their projects. I have never heard a complaint about this book and that is REALLY unusual with a statistics book.
Walker writes short chapters centered around common statistical methods. He gives a clean paragraph or two saying why you would use a statistic. Then he writes-up a little math, with the algebra usually worked out. After that the vast majority of the chapters are completed examples with datasets, code and output. The code and output are annotated with notes and numbered labels so you can quickly figure out what each part of the output and code means (in clear English).
If you get stuck in an overly theoretical statistics class get this book and you will be able to actually do the work you need for biostatistics projects that use SAS.
0 of 0 people found the following review helpful.
Five Stars
By Luming.Wu
Very nice one
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