Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Second Edition (Chapman & Hall/CRC Interdisciplinary Statistics)

Book Detail
Edition: 2
Release: 2013-03-26
Publisher: Chapman and Hall/CRC
Binding: Hardcover
ISBN/ASIN: 1466504811
Format: hardcover, kindle, PDF, EPUB

Bayesian Disease Mapping pdf
Description

Since the publication of the first edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas. Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Second Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications. A biostatistics professor and WHO advisor, the author illustrates the use of Bayesian hierarchical modeling in the geographical analysis of disease through a range of real-world datasets. New to the Second Edition Three new chapters on regression and ecological analysis, putative hazard modeling, and disease map surveillance Expanded material on case event modeling and spatiotemporal analysis New and updated examples Two new appendices featuring examples of integrated nested Laplace approximation (INLA) and conditional autoregressive (CAR) mode Download Bayesian Disease Mapping for free via rapidshare, mediafire, 4shared, dropBox, uploading, fileserve

Download Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Second Edition (Chapman & Hall/CRC Interdisciplinary Statistics) pdf

Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology (Chapman & Hall/CRC Interdisciplinary Statistics) Pdf

Book Detail
Edition: 1
Release: 2008-08-05
Publisher: Chapman and Hall/CRC
Binding: Hardcover
ISBN/ASIN: 1584888407
Format: hardcover, kindle, PDF, EPUB

Bayesian Disease Mapping pdf
Description

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 modeling, including Markov chain Monte Carlo methods, Gibbs sampling, the Metropolis–Hastings algorithm, goodness-of-fit measures, and residual diagnostics. It also focuses on special topics, such as cluster detection; space-time modeling; and multivariate, survival, and longitudinal analyses. The author explains how to apply these methods to disease mapping using numerous real-world data sets pertaining to cancer, asthma, epilepsy, foot and mouth disease, influenza, and other diseases. In the appendices, he shows how R and WinBUGS can be useful tools in data manipulation and simulation. Applying Bayesian methods to the modeling of georef Download Bayesian Disease Mapping for free via rapidshare, mediafire, 4shared, dropBox, uploading, fileserve

Download Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology (Chapman & Hall/CRC Interdisciplinary Statistics) pdf