» Common Statistical Methods for Clinical Research with SAS Examples, Second Edition
Common Statistical Methods for Clinical Research with SAS Examples, Second Edition Details
Binding: PaperbackDewey Decimal Number: 610.727
EAN: 9781590470404
ISBN: 1590470400
Label: SAS Publishing
Manufacturer: SAS Publishing
Number Of Items: 1
Number Of Pages: 488
Publication Date: 2002-07-15
Publisher: SAS Publishing
Studio: SAS Publishing
Items related to Common Statistical Methods for Clinical Research with SAS Examples, Second Edition
Common Statistical Methods for Clinical Research with SAS Examples, Second Edition Reviews
Customer Rating:




Summary: A favorite
Comment: 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 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.
Customer Rating:





Summary: great introduction to biostatistics in context of SAS implementation
Comment: 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.
Customer Rating:





Summary: Statistical Methods with SAS Examples
Comment: Great book to show the two main pieces of biostatistical studies; choosing the best statistical design for the clinical study, and how to run data points through SAS software to produce statistical output. Calculations by hand for the statistics are also presented, so the reader can see that the software yields the same answer. Best book I have seen showing explicitly how conduct a clinical research statistical study.
Customer Rating:





Summary: decent book
Comment: 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.
Customer Rating:





Summary: One of a kind
Comment: 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.
Editorial Review for Common Statistical Methods for Clinical Research with SAS Examples, Second Edition:
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.Supports releases 6.08 and higher of SAS software.



