Case Studies in Bayesian Statistics: Volume V (Lecture Notes in Statistics, 162) - Softcover

 
9780387951690: Case Studies in Bayesian Statistics: Volume V (Lecture Notes in Statistics, 162)

Synopsis

The 5th Workshop on Case Studies in Bayesian Statistics was held at the Carnegie Mellon University campus on September 24-25, 1999. As in the past, the workshop featured both invited and contributed case studies. The former were presented and discussed in detail while the latter were presented in poster format. This volume contains the three invited case studies with the accompanying discussion as well as ten contributed pa­ pers selected by a refereeing process. The majority of case studies in the volume come from biomedical research. However, the reader will also find studies in education and public policy, environmental pollution, agricul­ ture, and robotics. INVITED PAPERS The three invited cases studies at the workshop discuss problems in ed­ ucational policy, clinical trials design, and environmental epidemiology, respectively. 1. In School Choice in NY City: A Bayesian Analysis ofan Imperfect Randomized Experiment J. Barnard, C. Frangakis, J. Hill, and D. Rubin report on the analysis of the data from a randomized study conducted to evaluate the New YorkSchool Choice Scholarship Pro­ gram. The focus ofthe paper is on Bayesian methods for addressing the analytic challenges posed by extensive non-compliance among study participants and substantial levels of missing data. 2. In Adaptive Bayesian Designs for Dose-Ranging Drug Trials D. Berry, P. Mueller, A. Grieve, M. Smith, T. Parke, R. Blazek, N.

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From the Publisher

This third volume of case studies presents detailed applications of Bayesian statistical analysis. Although the applications are from a variety of areas, the emphasis in this volume is on econometrics. The first two volumes have proved to be valuable references for statistical instructors and data analysts.

Review

From the reviews:

TECHNOMETRICS

"...well written and can be appreciated by those with little biology background...In general, I found many of the papers collected in this book interesting...readers who are interested in applying Bayesian analysis in real case studies may find this book useful. One might consider using this book as supplementary material in graduate-level seminar courses on Bayesian data analysis."

Journal of the American Statistical Association, June 2004

"The volume as a whole illustrates the range of models that can now be fitted following the Markov chain Monte Carlo revolution, assess the behavior of posterior summaries under model misspecifications."

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