A Bayesian Partial Membership Model for Multiple Exposures with Uncertain Group Memberships.

ABSTRACT: We present a Bayesian partial membership model that estimates the associations between an outcome, a small number of latent variables, and multiple observed exposures where the number of latent variables is specified a priori. We assign one observed exposure as the sentinel marker for each latent variable. The model allows non-sentinel exposures to have complete membership in one latent group, or partial membership across two or more latent groups. MCMC sampling is used to determine latent group partial memberships for the non-sentinel exposures, and estimate all model parameters. We compare the performance of our model to competing approaches in a simulation study and apply our model to inflammatory marker data measured in a large mother-child cohort of the Seychelles Child Develop

SUBMITTER: Zavez AE 

PROVIDER: S-EPMC11530226 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature