An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian approach to data sets involving inferences for collections of related units or variables, and in methods where parameters can be treated as random collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian hierarchical methods.

The new edition is a revision of the book Applied Bayesian Hierarchical Methods. It maintains a focus on applied modelling and data analysis, but now using entirely R-based Bayesian computing options. It has been updated with a new chapter on regression for causal effects, and one on computing options and strategies. This latter chapter is particularly important, due to recent advances in Bayesian computing and estimation, including the development of rjags and rstan. It also features updates throughout with new examples.

The examples exploit and illustrate the broader advantages of the R computing environment, while allowing readers to explore alternative likelihood assumptions, regression structures, and assumptions on prior densities.

Features:

Provides a comprehensive and accessible overview of applied Bayesian hierarchical modelling

Includes many real data examples to illustrate different modelling topics

R code (based on rjags, jagsUI, R2OpenBUGS, and rstan) is integrated into the book, emphasizing implementation

Software options and coding principles are introduced in new chapter on computing

Programs and data sets available on the book’s website

About the Author

Peter Congdon is Research Professor in Quantitative Geography and Health Statistics at Queen Mary, University of London.

"About this title" may belong to another edition of this title.

Store Description

Visit Seller's Storefront

Seller's business information

Edward Bowditch Ltd
Exstowe, Exton, Exeter, EX3 0PP, United Kingdom

Sale & Shipping Terms

Terms of Sale

Legal entity name: Edward Bowditch Ltd
Legal entity form: Limited company
Business correspondence address: Exstowe, Exton, Exeter, EX3 0PP
Company registration number: 04916632
VAT registration: GB834241546
Authorised representative: Mr. E. Bowditch

Shipping Terms

Orders usually dispatched within two working days. Please note that at this time all domestic United Kingdom orders are sent by trackable UPS courier, we choose not to offer a lower cost alternative.