A Bayesian approach to investigate life course hypotheses involving continuous exposures.

ABSTRACT:

Background

Different hypotheses have been proposed in life course epidemiology on how a time-varying exposure can affect health or disease later in life. Researchers are often interested in investigating the probability of these hypotheses based on observed life course data. However, current techniques based on model/variable selection do not provide a direct estimate of this probability. We propose an alternative technique for a continuous exposure, using a Bayesian approach that has specific advantages, to investigate which life course hypotheses are supported by the observed data.

Methods

We demonstrate the technique, the relevant life course exposure model (RLM), using simulations. We also analyse data from a case-control study on risk factors of oral cancer, with repeat

SUBMITTER: Madathil S 

PROVIDER: S-EPMC6208282 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature