Document Type
Article
Publication Date
2011
Abstract
We develop a new Bayesian two-stage space-time mixture model to investigate the effects of air pollution on asthma. The two-stage mixture model proposed allows for the identification of temporal latent structure as well as the estimation of the effects of covariates on health outcomes. In the paper, we also consider spatial misalignment of exposure and health data. A simulation study is conducted to assess the performance of the 2-stage mixture model. We apply our statistical framework to a county-level ambulatory care asthma data set in the US state of Georgia for the years 1999-2008.
Recommended Citation
Lawson, Andrew B.; Choi, Jungsoon; Cai, Bo; Hossain, Md. Monir; Kirby, Russell S.; and Liu, Jihong, "Bayesian 2-Stage Space-Time Mixture Modeling with Spatial Misalignment of the Exposure in Small Area Health Data" (2011). MUSC Department of Public Health Sciences Working Papers. 4.
https://medica-musc.researchcommons.org/workingpapers/4