Using R for Bayesian Spatial and Spatio-Temporal Health Modeling

Name: Using R for Bayesian Spatial and Spatio-Temporal Health Modeling
SKU: GC-9896786533
Availability: InStock

$30.00

Progressively more and more attention has been paid to how location affects health outcomes. The area of disease mapping 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. Using R for Bayesian Spatial and Spatio-Temporal Health Modeling provides a major resource for those interested in applying Bayesian methodology in small area health data studies. Features: Review of R graphics relevant to spatial health data Overview of Bayesian methods and Bayesian hierarchical modeling as applied to spatial data Bayesian Computation and goodness-of-fit Review of basic Bayesian disease mapping models Spatio-temporal modeling with MCMC and INLA Special topics include multivariate models, survival analysis, missing data, measurement error, variable selection, individual event modeling, and infectious disease modeling Software for fitting models based on BRugs, Nimble, CARBayes and INLA Provides code relevant to fitting all examples throughout the book at a supplementary website The book fills a void in the literature and available software, providing a crucial link for students and professionals alike to engage in the analysis of spatial and spatio-temporal health data from a Bayesian perspective using R. The book emphasizes the use of MCMC via Nimble, BRugs, and CARBAyes, but also includes INLA for comparative purposes. In addition, a wide range of packages useful in the analysis of geo-referenced spatial data are employed and code is provided. It will likely become a key reference for researchers and students from biostatistics, epidemiology, public health, and environmental science. Additional ISBNs 0367760673, 0367490129, 1003043992, 9780367760670, 9780367490126, 9781003043997Using R for Bayesian Spatial and Spatio-Temporal Health Modeling 1st Edition is written by Andrew B. Lawson and published by Chapman & Hall. ISBNs for Using R for Bayesian Spatial and Spatio-Temporal Health Modeling are 9781000376722, 1000376729 and the print ISBNs are 9780367760670, 0367760673. Additional ISBNs include 0367760673, 0367490129, 1003043992, 9780367760670, 9780367490126, 9781003043997.

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Progressively more and more attention has been paid to how location affects health outcomes.

The area of disease mapping 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. Using R for Bayesian Spatial and Spatio-Temporal Health Modeling provides a major resource for those interested in applying Bayesian methodology in small area health data studies. Features: Review of R graphics relevant to spatial health data Overview of Bayesian methods and Bayesian hierarchical modeling as applied to spatial data Bayesian Computation and goodness-of-fit Review of basic Bayesian disease mapping models Spatio-temporal modeling with MCMC and INLA Special topics include multivariate models, survival analysis, missing data, measurement error, variable selection, individual event modeling, and infectious disease modeling Software for fitting models based on BRugs, Nimble, CARBayes and INLA Provides code relevant to fitting all examples throughout the book at a supplementary website The book fills a void in the literature and available software, providing a crucial link for students and professionals alike to engage in the analysis of spatial and spatio-temporal health data from a Bayesian perspective using R. The book emphasizes the use of MCMC via Nimble, BRugs, and CARBAyes, but also includes INLA for comparative purposes. In addition, a wide range of packages useful in the analysis of geo-referenced spatial data are employed and code is provided. It will likely become a key reference for researchers and students from biostatistics, epidemiology, public health, and environmental science. Additional ISBNs 0367760673, 0367490129, 1003043992, 9780367760670, 9780367490126, 9781003043997Using R for Bayesian Spatial and Spatio-Temporal Health Modeling 1st Edition is written by Andrew B. Lawson and published by Chapman & Hall. ISBNs for Using R for Bayesian Spatial and Spatio-Temporal Health Modeling are 9781000376722, 1000376729 and the print ISBNs are 9780367760670, 0367760673. Additional ISBNs include 0367760673, 0367490129, 1003043992, 9780367760670, 9780367490126, 9781003043997.