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A common spatial factor analysis model for measured neighborhood-level characteristics: The Multi-Ethnic Study of
Rachel C Nethery1, Joshua L Warren2, Amy H Herring1
1University of North Carolina at Chapel Hill, Department of Biostatistics, Gillings School of Global Public Health, Hall, CB # 7420, Chapel USA.
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.
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