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Analysis of disease risks using ancillary risk factors, with application to job–exposure matrices
Author(s) -
Gilks Walter R.,
Richardson Sylvia
Publication year - 1992
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780111104
Subject(s) - logistic regression , disease , statistics , population , computer science , epidemiology , econometrics , job exposure matrix , regression analysis , risk factor , environmental health , risk analysis (engineering) , medicine , mathematics
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.