Spatiotemporal multivariate mixture models for Bayesian model selection in disease mapping.
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ABSTRACT:
SUBMITTER: Lawson AB
PROVIDER: S-EPMC5722237 | biostudies-literature | 2017 Dec
REPOSITORIES: biostudies-literature
Publications
Spatiotemporal multivariate mixture models for Bayesian model selection in disease mapping.
Lawson A B AB Carroll R R Faes C C Kirby R S RS Aregay M M Watjou K K
Environmetrics 20170925 8
It is often the case that researchers wish to simultaneously explore the behavior of and estimate overall risk for multiple, related diseases with varying rarity while accounting for potential spatial and/or temporal correlation. In this paper, we propose a flexible class of multivariate spatio-temporal mixture models to fill this role. Further, these models offer flexibility with the potential for model selection as well as the ability to accommodate lifestyle, socio-economic, and physical envi ...[more]
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