Using R for Bayesian Spatial and Spatio-Temporal Health Modeling av Andrew B. (University of South Carolina Columbia USA) Lawson

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<P>Progressively more and more attention has been paid to how location affects health outcomes. The area of <I>disease mapping</I> focusses on these problems, and the Bayesian paradigm has a major role to play in the understanding of the complex interplay of context and individual predisposition in such studies of disease. <B><I>Using R for Bayesian Spatial and Spatio-Temporal Health Modeling</B></I> provides a major resource for those interested in applying Bayesian methodology in small area health data studies.</P><P></P><B><P>Features:</P></B><P></P><UL><P><LI>Review of R graphics relevant to spatial health data</LI><P></P><P><LI>Overview of Bayesian methods and Bayesian hierarchical modeling as applied to spatial data</LI><P></P><P><LI>Bayesian Computation and goodness-of-fit</LI><P></P><P><LI>Review of basic Bayesian disease mapping models </LI><P></P><P><LI>Spatio-temporal modeling with MCMC and INLA</LI><P></P><P><LI>Special topics include multivariate models, survival analysis,