A Bayesian approach to comparing common models of life-course epidemiology.

ABSTRACT:

Background

Life-course epidemiology studies people's health over long periods, treating repeated measures of their experiences (usually risk factors) as predictors or causes of subsequent morbidity and mortality. Three hypotheses or models often guide the analyst in assessing these sequential risks: the accumulation model (all measurement occasions are equally important for predicting the outcome), the critical period model (only one occasion is important) and the sensitive periods model (a catch-all model for any other pattern of temporal dependence).

Methods

We propose a Bayesian omnibus test of these three composite models, as well as post hoc decompositions that identify their best respective sub-models. We test the approach via simulations, before presenting an empirica

SUBMITTER: Chumbley J 

PROVIDER: S-EPMC8580273 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature