A Bayesian Latent Model with Spatio-temporally Varying Coefficients in Low Birth Weight Incidence Data
Document Type
Article
Publication Date
2012
Keywords
Low birth weight, spatial cluster, spatio-temporal mixture model, latent model
Digital Object Identifier (DOI)
https://doi.org/10.1177/0962280212446318
Abstract
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.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Statistical Methods in Medical Research, v. 21, issue 5, p. 445-456
Scholar Commons Citation
Choi, Jungsoon; Lawson, Andrew B.; Cai, Bo; Hossain, Md Monir; Kirby, Russell S.; and Liu, Jihong, "A Bayesian Latent Model with Spatio-temporally Varying Coefficients in Low Birth Weight Incidence Data" (2012). Community and Family Health Faculty Publications. 79.
https://digitalcommons.usf.edu/cfh_facpub/79
