Alcohol Abuse Disorder Prevalence and its Distribution Across Portugal
A Disease Mapping Approach
DOI:
https://doi.org/10.57805/revstat.v13i1.165Keywords:
alcohol abuse, Bayesian hierarchical models, disease mapping, generalized linear models, small area estimationAbstract
Disease mapping is linked to two other scientific areas: small area estimation and ecological-spatial regression. This paper reviews similarities and differences among them. Bayesian hierarchical models are typically used in this context, using a combination of covariate data and a set of spatial random effects to represent the risk surface. The random effects are typically modeled by a conditional autoregressive prior distribution, and a number of alternative specifications have been proposed in the literature. The four models assessed here are applied to a study on alcohol abuse in Portugal, using data collected by the World Mental Health Survey Initiative.
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Copyright (c) 2015 REVSTAT-Statistical Journal
This work is licensed under a Creative Commons Attribution 4.0 International License.