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Analyze Repeated Measures Studies Using Bayesian Techniques
Going beyond standard non-Bayesian books, Bayesian Methods for Repeated Measures presents the main ideas for the analysis of repeated measures and associated designs from a Bayesian viewpoint. It describes many inferential methods for analyzing repeated measures in various scientific areas, especially biostatistics.
The author takes a practical approach to the analysis of repeated measures. He bases all the computing and analysis on the WinBUGS package, which provides readers with a platform that efficiently uses prior information. The book includes the WinBUGS code needed to implement posterior analysis and offers the code for download online.
Accessible to both graduate students in statistics and consulting statisticians, the book introduces Bayesian regression techniques, preliminary concepts and techniques fundamental to the analysis of repeated measures, and the most important topic for repeated measures studies: linear models. It presents an in-depth explanation of estimating the mean profile for repeated measures studies, discusses choosing and estimating the covariance structure of the response, and expands the representation of a repeated measure to general mixed linear models. The author also explains the Bayesian analysis of categorical response data in a repeated measures study, Bayesian analysis for repeated measures when the mean profile is nonlinear, and a Bayesian approach to missing values in the response variable.
- Sales Rank: #4151685 in Books
- Published on: 2015-08-04
- Original language: English
- Number of items: 1
- Dimensions: 9.30" h x 1.30" w x 6.00" l, .0 pounds
- Binding: Hardcover
- 568 pages
About the Author
Lyle D. Broemeling has 30 years of experience as a biostatistician. He has been a professor at the University of Texas Medical Branch at Galveston, the University of Texas School of Public Health at Houston, and the University of Texas MD Anderson Cancer Center. He is also the author of several books, including Bayesian Methods in Epidemiology. His research interests include the analysis of repeated measures and Bayesian methods for assessing medical test accuracy and inter-rater agreement.
Most helpful customer reviews
0 of 0 people found the following review helpful.
Leaves a lot desiring
By Djam Leelii
While the book says that WinBugs code for all examples are on the author's blogspot site, many any aren't there (and several that aren't even discussed in the book ARE there). Worse, the datasets aren't even online, meaning you have to HAND TYPE pages of them if you want to follow many of the examples. Also misleading is that the book refers to the appendices - which are not in the book - but doesn't mention that they're on blogspot (well, at least so it seems, as they're not numbered online). Also, the extensive formulas used in the book imply that the reader has care or familiarity with such matters. While that might be your case, if not, it's cumbersome and could all have been moved to appendices. Lastly, while WinBugs is fine software, it's been out of development since 2008. A much better choice would have been R or even SPSS.
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