Bayesian variable selection for understanding mixtures in environmental exposures.

ABSTRACT: Social and environmental stressors are crucial factors in child development. However, there exists a multitude of measurable social and environmental factors-the effects of which may be cumulative, interactive, or null. Using a comprehensive cohort of children in North Carolina, we study the impact of social and environmental variables on 4th end-of-grade exam scores in reading and mathematics. To identify the essential factors that predict these educational outcomes, we design new tools for Bayesian linear variable selection using decision analysis. We extract a predictive optimal subset of explanatory variables by coupling a loss function with a novel model-based penalization scheme, which leads to coherent Bayesian decision analysis and empirically improves variable selection, estimatio

SUBMITTER: Kowal DR 

PROVIDER: S-EPMC8440371 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature