| Literature DB >> 26372887 |
Rachel C Nethery1, Joshua L Warren2, Amy H Herring3, Kari A B Moore4, Kelly R Evenson5, Ana V Diez-Roux6.
Abstract
The purpose of this study was to reduce the dimensionality of a set of neighborhood-level variables collected on participants in the Multi-Ethnic Study of Atherosclerosis (MESA) while appropriately accounting for the spatial structure of the data. A common spatial factor analysis model in the Bayesian setting was utilized in order to properly characterize dependencies in the data. Results suggest that use of the spatial factor model can result in more precise estimation of factor scores, improved insight into the spatial patterns in the data, and the ability to more accurately assess associations between the neighborhood environment and health outcomes.Entities:
Keywords: Bayesian analysis; Body mass index; Factor analysis; Spatial statistics
Mesh:
Year: 2015 PMID: 26372887 PMCID: PMC4679666 DOI: 10.1016/j.healthplace.2015.08.009
Source DB: PubMed Journal: Health Place ISSN: 1353-8292 Impact factor: 4.078