Bayesian Models for Categorical Data

✍ Scribed by Peter Congdon

• Publisher: Wiley
• Year: 2005
• Tongue: English
• Leaves: 447
• Series: Wiley Series in Probability and Statistics
• Edition: 1
• Category: Library

✦ Synopsis

The use of Bayesian methods for the analysis of data has grown substantially in areas as diverse as applied statistics, psychology, economics and medical science. Bayesian Methods for Categorical Data sets out to demystify modern Bayesian methods, making them accessible to students and researchers alike. Emphasizing the use of statistical computing and applied data analysis, this book provides a comprehensive introduction to Bayesian 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 discrete data. Features discussion of univariate and multivariate techniques.* Provides a set of downloadable worked examples with documented WinBUGS code, available from an ftp site.The author's previous 2 bestselling titles provided a comprehensive introduction to the theory and application of Bayesian models. Bayesian Models for Categorical Data continues to build upon this foundation by developing their application to categorical, or discrete data - one of the most common types of data available. The author's clear and logical approach makes the book accessible to a wide range of students and practitioners, including those dealing with categorical data in medicine, sociology, psychology and epidemiology.

✦ Table of Contents

Cover
......Page 1
Contents
......Page 6
Preface
......Page 12
1. Principles of Bayesian inference
......Page 14
2. Model comparison and choice
......Page 42
3. Regression for metric outcomes
......Page 68
4. Models for binary and count outcomes
......Page 126
5. Further questions in binomial and count regression
......Page 168
6. Random effect and latent variable models for multicategory outcomes
......Page 210
7. Ordinal regression
......Page 248
8. Discrete spatial data
......Page 280
9. Time series models for discrete variables
......Page 302
10. Hierarchical and panel data models
......Page 334
11. Missing-data models
......Page 392
Index
......Page 428
Wiley series in probability and statistics
......Page 440

✦ Subjects

Финансово-экономические дисциплины;Статистический анализ экономических данных;