A Bayesian latent model with spatio-temporally varying coefficients in low birth weight incidence data

作者：Choi Jungsoon^*; Lawson Andrew B; Cai Bo; Hossain Md Monir; Kirby Russell S; Liu Jihong

来源：Statistical Methods in Medical Research, 2012, 21(5): 445-456.

DOI：10.1177/0962280212446318

• Low birth weight
• spatial cluster
• spatio-temporal mixture model
• latent model

In spatial epidemiology studies, the effects of covariates on adverse health outcomes could vary over space and time so examining the spatio-temporally varying effects is useful. In particular, the association between covariates and health outcomes could have locally different temporal patterns. In this article, we develop a Bayesian spatio-temporal latent model to identify spatial clusters in each of which covariate effects have homogeneous temporal patterns as well as estimate heterogeneous temporal effects of covariates depending on spatial groups. We compare the proposed model to several alternative models to assess the performance of the proposed model in terms of a range of model assessment measures. Low birth weight incidence data in Georgia for the years 1997-2006 are used.

• 出版日期2012-10