Bayesian modeling of time-varying and waning exposure effects.

Published

Journal Article

In epidemiologic studies, there is often interest in assessing the association between exposure history and disease incidence. For many diseases, incidence may depend not only on cumulative exposure, but also on the ages at which exposure occurred. This article proposes a flexible Bayesian approach for modeling age-varying and waning exposure effects. The Cox model is generalized to allow the hazard of disease to depend on an integral, across the exposed ages, of a piecewise polynomial function of age, multiplied by an exponential decay term. Linearity properties of the model facilitate posterior computation via a Gibbs sampler, which generalizes previous algorithms for Cox regression with time-dependent covariates. The approach is illustrated by an application to the study of protective effects of breastfeeding on incidence of childhood asthma.

Full Text

Duke Authors

Cited Authors

  • Dunson, DB; Chulada, P; Arbes, SJ

Published Date

  • March 2003

Published In

Volume / Issue

  • 59 / 1

Start / End Page

  • 83 - 91

PubMed ID

  • 12762444

Pubmed Central ID

  • 12762444

Electronic International Standard Serial Number (EISSN)

  • 1541-0420

International Standard Serial Number (ISSN)

  • 0006-341X

Digital Object Identifier (DOI)

  • 10.1111/1541-0420.00010

Language

  • eng