Bayesian Approaches to Clinical Trials and Health-Care Evaluation

David J. Spiegelhalter 지음

Wiley 2004년 05월 05일 출간

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READ ALL ABOUT IT!David Spiegelhalter has recently joined the ranks of Isaac Newton, Charles Darwin and Stephen Hawking by becoming a fellow of the Royal Society.Originating from the Medical Research Council-s biostatistics unit, David has played a leading role in the Bristol heart surgery and Harold Shipman inquiries.Order a copy of this author-s comprehensive text TODAY!The Bayesian approach involves synthesising data and judgement in order to reach conclusions about unknown quantities and make predictions. Bayesian methods have become increasingly popular in recent years, notably in medical research, and although there are a number of books on Bayesian analysis, few cover clinical trials and biostatistical applications in any detail. Bayesian Approaches to Clinical Trials and Health-Care Evaluation provides a valuable overview of this rapidly evolving field, including basic Bayesian ideas, prior distributions, clinical trials, observational studies, evidence synthesis and cost-effectiveness analysis.Covers a broad array of essential topics, building from the basics to more advanced techniques.Illustrated throughout by detailed case studies and worked examplesIncludes exercises in all chaptersAccessible to anyone with a basic knowledge of statisticsAuthors are at the forefront of research into Bayesian methods in medical researchAccompanied by a Web site featuring data sets and worked examples using Excel and WinBUGS - the most widely used Bayesian modelling packageBayesian Approaches to Clinical Trials and Health-Care Evaluation is suitable for students and researchers in medical statistics, statisticians in the pharmaceutical industry, and anyone involved in conducting clinical trials and assessment of health-care technology.

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Preface.List of examples.1. Introduction.1.1 What are Bayesian methods?1.2 What do we mean by &-health-care evaluation&-?1.3 A Bayesian approach to evaluation.1.4 The aim of this book and the intended audience.1.5 Structure of the book.2. Basic Concepts from Traditional Statistical Analysis.2.1 Probability.2.1.1 What is probability?2.1.2 Odds and log-odds.2.1.3 Bayes theorem for simple events.2.2 Random variables, parameters and likelihood.2.2.1 Random variables and their distributions.2.2.2 Expectation, variance, covariance and correlation.2.2.3 Parametric distributions and conditional independence.2.2.4 Likelihoods.2.3 The normal distribution.2.4 Normal likelihoods.2.4.1 Normal approximations for binary data.2.4.2 Normal likelihoods for survival data.2.4.3 Normal likelihoods for count responses.2.4.4 Normal likelihoods for continuous responses.2.5 Classical inference.2.6 A catalogue of useful distributions*.2.6.1 Binomial and Bernoulli.2.6.2 Poisson.2.6.3 Beta.2.6.4 Uniform.2.6.5 Gamma.2.6.6 Root-inverse-gamma.2.6.7 Half-normal.2.6.8 Log-normal.2.6.9 Student&-s t.2.6.10 Bivariate normal.2.7 Key points.Exercises.3. An Overview of the Bayesian Approach.3.1 Subjectivity and context.3.2 Bayes theorem for two hypotheses.3.3 Comparing simple hypotheses: likelihood ratios and Bayes factors.3.4 Exchangeability and parametric modelling*.3.5 Bayes theorem for general quantities.3.6 Bayesian analysis with binary data.3.6.1 Binary data with a discrete prior distribution.3.6.2 Conjugate analysis for binary data.3.7 Bayesian analysis with normal distributions.3.8 Point estimation, interval estimation and interval hypotheses.3.9 The prior distribution.3.10 How to use Bayes theorem to interpret trial results.3.11 The &-credibility&- of significant trial results*.3.12 Sequent

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"This is a terrific book and should be on the shelf of every professional that works in clinical trials or health-care evaluation. It gives a thorough pragmatic introduction to Bayesian methods for health-care interventions, provides many example along with data and software to reproduce the analyses, guides readers to areas where Bayesian methods are particularly valuable, and includes an excellent set of exercises." (Journal of the American Statistical Association, June 2009)"Bayesian Approaches to Clinical Trials and Health-Care Evaluation' is a clear and comprehensive text for biostatisticians who want to understand and apply Bayesian statistical methods to clinical research." (Journal of Clinical Best Practices, Nov 2008)"…an indispensable resource for all students and investigators who plan to incorporate Bayesian methods into their research." (The Annals of Pharmacotherapy, January 2005)"...a valuable resource for libraries, and those who are involved in quantitative health care evaluation..." (Royal Statistical Society, Vol.168, No.1, January 2005)"...The technical material is presented in an accessible style, and the examples given clearly illustrate the principles under discussion..." (Short Book Reviews, Vol.24, No.3, December 2004)"...Bayesian analysis seems set to reach a wider audience with the publication of [this] introductory level text..." (Financial Times, 16 April 2004)"...very well laid-out and easy to follow...a very good resource for teaching students..." (Statistical Methods in Medical Research, Vol 14, 2005)"I would use with pleasure and interest this book as a textbook..." (Metron Journal, Vol.63, No.2, 2005)"...I can pay the authors no higher tribute than to say that I would be proud to have written this book. It is elegant and it is destined to becoming a classic in the field." (Statistics in Medicine, 15th July 2005)"...a generous supply of ex

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저자(글) David J. Spiegelhalter