Bayesian Methods for Data Analysis

! would appeal to a practising statistician in the pharmaceutical industry. ! [Examples] are clearly worked through from start to finish with hints on presentation of results. ! I would recommend this book to somebody who is learning Bayesian methods and it would also be useful for those with more experience. ! It should sit alongside other good Bayesian book in anybody's collection. --Alun Bedding, Pharmaceutical Statistics, 2010 ! 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