A latent functional approach for modeling the effects of multidimensional exposures on disease risk.

ABSTRACT: Understanding the relationships between exposure and disease incidence is an important problem in environmental epidemiology. Typically, a large number of these exposures are measured, and it is found either that a few exposures transmit risk or that each exposure transmits a small amount of risk, but, taken together, these may pose a substantial disease risk. Further, these exposure effects can be nonlinear. We develop a latent functional approach, which assumes that the individual effect of each exposure can be characterized as one of a series of unobserved functions, where the number of latent functions is less than or equal to the number of exposures. We propose Bayesian methodology to fit models with a large number of exposures and show that existing Bayesian group LASSO approaches ar

SUBMITTER: Kim S 

PROVIDER: S-EPMC11984352 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature