Product Description:
Glenn Walker and Jack Shostak's Common Statistical Methods for Clinical Research with SAS Examples, Third Edition, is a 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. Straightforward and easy to use as either a text or a reference, the book is full of practical examples from clinical research to illustrate both statistical and SAS methodology. Each example is worked out completely, step by step, from the raw data.
Common Statistical Methods for Clinical Research with SAS Examples, Third Edition, is an applications book with minimal theory. Each section begins with an overview helpful to nonstatisticians and then drills down into details that will be valuable to statistical analysts and programmers. Further details, as well as bonus information and a guide to further reading, are presented in the extensive appendices. This text is a one-source guide for statisticians that documents the use of the tests used most often in clinical research, with assumptions, details, and some tricks--all in one place.
Summary: The perfect place to startRating: 5
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.
