摘要:Disease mapping is linked to two other scientific areas: small area estimation and ecological-spatial regression. This paper reviews similarities and di.erences among them. Bayesian hierarchical models are typically used in this context, using a com- bination of covariate data and a set of spatial random e.ects to represent the risk surface. The random e.ects are typically mo deled by a conditional autoregressive prior distribution, and a number of alternative specifications have been proposed in the literature. The four mo dels assessed here are applied to a study on alcohol abuse in Portugal, using data collected by the World Mental Health Survey Initiative.
关键词:alcohol abuse; Bayesian hierarchical models; disease mapping; generalized linear ; models; small area estimation