Subgroup Analyses and Effect Modification with Bayesian Kernel Machine Regression.

ABSTRACT: There is substantial interest in estimating the health effects of exposure to environmental mixtures. Bayesian kernel machine regression (BKMR) has emerged as a popular tool for mixture analyses. The health effects of environmental exposures, including mixture exposures, often differ among subpopulations. However, there is little guidance on how to assess such heterogeneity for mixture effects. We provide tools and guidance to conduct BKMR analyses with effect modification, including estimating group-specific effects and between-group differences in effects. We propose a new group-separable BKMR variant for mixture analyses with effect modification by a categorical variable. We compare this new method to a stratified analysis and to a model that includes the categorical modifier directly i

SUBMITTER: Demateis D 

PROVIDER: S-EPMC12758637 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature