WITHDRAWN A Bayesian Multilayered Simplex Factor Regression Model for Complex Epidemiological Data

Dietary acculturation can greatly impact chronic disease progression in migrant populations. Yet modeling the interrelationship between a large set of multivariate acculturation exposures and multivariate dietary consumption outcomes is challenging. Mixed membership models are useful for identifying the underlying dietary patterns by positing individuals to a few outcome subgroups of varying degrees, but difficulties arise when these outcomes relate to latent exposure subgroups. We propose a new multilayered simplex factor regression model that simultaneously derives latent acculturation exposure and dietary outcome patterns while capturing the exposure-outcome relationship. The relationship is modeled via a stick-breaking multivariate logistic regression on the individual membership scores, allowing for easy introduction of auxiliary information and flexible choices of the number of subgroups. We discuss model identifiability conditions and demonstrate this method on a migrant population in the United States.

Bayesian methods

Latent class models

Grade of membership models

Multivariate categorical data

Epidemiology