The third edition of "Bayesian Methods for Data Analysis" has been updated to provide a more accessible introduction to the foundations of Bayesian analysis along with a stronger focus on applications, including case studies in biostatistics, epidemiology, and genetics.
This edition features a new chapter on Bayesian design that presents Bayesian clinical trials and special topics such as missing data and causality. With an emphasis on computation, there is also expanded coverage of WinBUGS, R, and BRugs. The book also contains additional exercises and solutions for courses on Bayesian data analysis and to assist in self-study for undergraduate students, graduate students, and researchers in statistics and biostatistics.
! this book will provide considerable value-added to one's library of Bayesian books. ! In the third edition, the authors directly integrate WinBUGS and R routines into their presentation of Bayesian methods and provide some new material along the way, in particular, an excellent discussion of Bayesian design. ! an excellent addition to the growing body of books on Bayesian analysis and is a must read for serious students of Bayesian statistics. --Psychometrika, Vol. 75, No. 2, June 2010 ! the third edition has more of a Bayesian flavor with comprehensive coverage of computational Bayesian statistics, including new additions of BUGS and R code throughout the book and reorganization or expansion of several chapters. ! I am glad to see that the software code and examples have also been made available on the website http://www.biostat.umn.edu/#brad/dataCL3.html so that users can truly enjoy easy access and convenience in reproducing the computations in the book. In summary, I think this is a very worthy edition and I highly recommend it as a textbook, and for people who deal with biostatistics problems regularly as a good introduction into the literature. Libraries which have the second edition are encouraged to buy this edition as well. --Journal of Applied Statistics, Vol. 37, No. 4, April 2010 ! the book contains some useful advice for practitioners. All the essential topics are covered ! Throughout the text one can find good practical advice on various implementation issues, and there is a whole chapter dedicated to case-studies. The chapter on Bayesian design provides very good coverage of some clinical trial design ideas that are receiving a considerable amount of interest in the pharmaceutical industry currently. This book, by two very experienced and knowledgeable Bayesians, is a valuable contribution to the growing literature on the practical application of Bayesian methods. ! --Journal of the Royal Statistical Society, Series A, Vol. 172, October 2009 ! A strength of this book is the numerous detailed examples that accompany the material in the text. ! This is a nice text and would be appropriate as a reference or teaching aid for a graduate-level course in applied Bayesian statistics. The emphasis on biomedical applications makes it a valuable resource for research in biostatistics. ! --Statistics in Medicine, 2009 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. ! 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. --Andrew Gelman, Columbia University, Amazon.com, 2008 with this reorganization of chapters in the third edition, I believe that the authors have made their material more accessible to an applied audience, and I would now seriously consider this book for my class. --James H. Albert, Bowling Green State University, Journal of the American Statistical Association, June 2009, Vol. 104, No. 486 Praise for the Previous Editions ! particularly recommend the book to practicing biometricians who want to explore the potential for using Bayesian methods in their own work. --Biometrics, Vol. 57, No. 3, September 2001 ! an important and timely addition to applied statistics ! the writing is excellent, and the authors are able to present an amazing amount of material cogently in [a] smaller book ! the reader reaps the benefits of being in the hands of a true master ! --Journal of American Statistical Association The writing is excellent and the worked examples are also excellent for understanding the methods. In summary, I recommend [it] for advanced graduate students and all research workers. --Olaf Berke, Computational Statistics & Data Analysis, January 2001
Approaches for statistical inference. The Bayes approach. Bayesian computation. Model criticism and selection. The empirical Bayes approach. Bayesian design. Special methods and models. Biostatistical methods. Case studies. Appendices.
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