Focusing on data commonly found in public health databases and clinical settings, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology provides an overview of the main areas of Bayesian hierarchical modeling and its application to the geographical analysis of disease. The book explores a range of topics in Bayesian inference and

part |2 pages

I Background

chapter 1|16 pages


chapter 2|16 pages

Bayesian Inference and Modeling

chapter 3|20 pages

Computational Issues

chapter 4|16 pages

Residuals and Goodness-of-Fit

part |2 pages

II Themes

chapter 6|32 pages

Disease Cluster Detection

chapter 7|34 pages

Ecological Analysis

chapter 8|16 pages

Multiple Scale Analysis

chapter 9|26 pages

Multivariate Disease Analysis

chapter 10|28 pages

Spatial Survival and Longitudinal Analysis

chapter 11|28 pages

Spatiotemporal Disease Mapping

chapter |24 pages

A Basic R and WinBUGS

chapter |12 pages

B Selected WinBUGS Code

chapter |2 pages

C R Code for Thematic Mapping