The use of Bayesian methods for the analysis of data has grownsubstantially in areas as diverse as applied statistics, psychology, economics and medical science. Bayesian Methods forCategorical Data sets out to demystify modern Bayesian methods, making them accessible to students and researchers alike.Emphasizing the use of statistical computing and applied dataanalysis, this book provides a comprehensive introduction toBayesian methods of categorical outcomes. * Reviews recent Bayesian methodology for categorical outcomes ...
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The use of Bayesian methods for the analysis of data has grownsubstantially in areas as diverse as applied statistics, psychology, economics and medical science. Bayesian Methods forCategorical Data sets out to demystify modern Bayesian methods, making them accessible to students and researchers alike.Emphasizing the use of statistical computing and applied dataanalysis, this book provides a comprehensive introduction toBayesian methods of categorical outcomes. * Reviews recent Bayesian methodology for categorical outcomes(binary, count and multinomial data). * Considers missing data models techniques and non-standard models(ZIP and negative binomial). * Evaluates time series and spatio-temporal models for discretedata. * Features discussion of univariate and multivariatetechniques. * Provides a set of downloadable worked examples with documentedWinBUGS code, available from an ftp site. The author's previous 2 bestselling titles provided a comprehensiveintroduction to the theory and application of Bayesian models.Bayesian Models for Categorical Data continues to build upon thisfoundation by developing their application to categorical, ordiscrete data - one of the most common types of data available. Theauthor's clear and logical approach makes the book accessible to awide range of students and practitioners, including those dealingwith categorical data in medicine, sociology, psychology andepidemiology.
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