A comparison of Bayesian hierarchical modeling with group-based exposure assessment in occupational epidemiology

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.