Analysis of disease risks using ancillary risk factors, with application to job-exposure matrices

Epidemiological studies of disease can make use of ancillary risk-factors, acquired from individuals outside the disease study. For example, several disease studies might use the same job-exposure matrix to quantify risks due to occupational exposure to industrial agents. We construct a graphical model to combine a logistic regression disease model with models for the ancillary data and the risk-factor distribution in the population. We estimate the graphical model using Gibbs sampling, and in simulations compare it with methods of direct substitution into logistic regression.