Bayesian disease mapping: hierarchical modeling in spatial epidemiology
Lawson, Andrew B.
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–Hastingsalgorithm, 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 applythese 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.
- ISBN: 978-1-58488-840-6
- Editorial: CRC
- Encuadernacion: Cartoné
- Páginas: 344
- Fecha Publicación: 05/08/2008
- Nº Volúmenes: 1
- Idioma: Inglés