Modeling a bivariate residential-workplace neighborhood effect when estimating the effect of proximity to fast-food establishments on body mass index.

ABSTRACT: Hierarchical modeling is the preferred approach of modeling neighborhood effects. When both residential and workplace neighborhoods are known, a bivariate (residential-workplace) neighborhood random effect that quantifies the extent that a neighborhood's residential and workplace effects are correlated may be modeled. However, standard statistical software for hierarchical models does not easily allow correlations between the random effects of distinct clustering variables to be incorporated. To overcome this challenge, we develop a Bayesian model and an accompanying estimation procedure that allows for correlated bivariate neighborhood effects and allows individuals to reside or work in multiple neighborhoods, cross-sectional and longitudinal heterogeneity between individuals, and serial

SUBMITTER: O'Malley AJ 

PROVIDER: S-EPMC6377346 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature