title: A comparison of Bayesian hierarchical modeling with group-based exposure assessment in occupational epidemiology.
abstract: We build a Bayesian hierarchical model for relating disease to a potentially harmful exposure, by using data from studies in occupational epidemiology, and compare our method with the traditional group-based exposure assessment method through simulation studies, a real data application, and theoretical calculation. We focus on cohort studies where a logistic disease model is appropriate and where group means can be treated as fixed effects. The results show a variety of advantages of the fully Bayesian approach and provide recommendations on situations where the traditional group-based exposure assessment method may not be suitable to use.
authors.affiliation: Department of Statistics, University of British Columbia, 333-6356 Agricultural Road, Vancouver, BC V6T 1Z2, Canada.
authors.forename: Li
authors.initials: L
authors.lastname: Xing
authors.forename: Igor
authors.initials: I
authors.lastname: Burstyn
authors.forename: David B
authors.initials: DB
authors.lastname: Richardson
authors.forename: Paul
authors.initials: P
authors.lastname: Gustafson
mesh_terms: D001499:Bayes Theorem; D015331:Cohort Studies; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D007938:Leukemia / Q000401:mortality; D008297:Male; D015233:Models, Statistical; D016273:Occupational Exposure / Q000009:adverse effects*; D011827:Radiation
keywords: Bayesian hierarchical model; MCMC; group-based exposure assessment; measurement error; missing data