Average Reviews:
(More customer reviews)I like this book a lot. It's not the book that I would've written, and that's a good thing. Buying Carlin and Louis along with our book will give you two perspectives on applied Bayesian statistics as it is practiced in the 21st century. Compared to our book, Carlin and Louis offer the following:
- Discussion of the debates over Bayesianism within the statistical community, culminating in chapter 5, which covers the links between Bayes, empirical Bayes, and frequentist methods of evaluating statistical procedures.
- A crisp presentation of Bayesian computation (chapter 5), which offers a different perspective than ours.
- A chapter on experimental design including several biomedical examples. This chapter should be useful to a lot of people, I think.
- Near the end of the book, discussion of several classes of models--longitudinal analysis, survival analysis, spatial models, clinical trials, and others--where I often think, "What's would a Bayesian do here?"
I don't think Carlin and Louis have made our own Bayesian Data Analysis obsolete but I do think their book is a great complement to ours, with a slightly different perspective, strong coverage of the theoretical issues of point and interval estimation, and a bunch of compelling biomedical examples.
Click Here to see more reviews about: Bayesian Methods for Data Analysis, Third Edition (Chapman & Hall/CRC Texts in Statistical Science)
Broadening its scope to nonstatisticians, Bayesian Methods for Data Analysis, Third Edition provides an accessible introduction to the foundations and applications of Bayesian analysis. Along with a complete reorganization of the material, this edition concentrates more on hierarchical Bayesian modeling as implemented via Markov chain Monte Carlo (MCMC) methods and related data analytic techniques. New to the Third Edition New data examples, corresponding R and WinBUGS code, and homework problems Explicit descriptions and illustrations of hierarchical modeling-now commonplace in Bayesian data analysisA new chapter on Bayesian design that emphasizes Bayesian clinical trialsA completely revised and expanded section on ranking and histogram estimationA new case study on infectious disease modeling and the 1918 flu epidemicA solutions manual for qualifying instructors that contains solutions, computer code, and associated output for every homework problem-available both electronically and in printIdeal for Anyone Performing Statistical Analyses Focusing on applications from biostatistics, epidemiology, and medicine, this text builds on the popularity of its predecessors by making it suitable for even more practitioners and students.
