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Název:		Bayesian disease mapping : hierarchical modeling in spatial epidemiology
Autor:		Lawson, Andrew
Rok vydání:		c2009
Identifikátory:		9781584888406

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Anotace:	Focusing on data commonly found in public health databases and clinical settings, <STRONG>Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology</STRONG> provides an overview of the main areas of Bayesian hierarchical modeling and its application to the geographical analysis of disease. <P>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. <P>Applying Bayesian methods to the modeling of georeferenced health data, <STRONG>Bayesian Disease Mapping</STRONG> proves that the application of these approaches to biostatistical problems can yield important insights into data.</P>
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