title: Bayesian analysis of a matched case-control study with expert prior information on both the misclassification of exposure and the exposure-disease association.
abstract: We propose a Bayesian adjustment for the misclassification of a binary exposure variable in a matched case-control study. The method admits a priori knowledge about both the misclassification parameters and the exposure-disease association. The standard Dirichlet prior distribution for a multinomial model is extended to allow separation of prior assertions about the exposure-disease association from assertions about other parameters. The method is applied to a study of occupational risk factors for new-onset adult asthma.
authors.affiliation: Department of Mathematics and Statistics, University of Saskatchewan, 106 Wiggins Road, Saskatoon, Saskatchewan, Canada S7N 5E6. liu@math.usask.ca
authors.forename: Juxin
authors.initials: J
authors.lastname: Liu
authors.forename: Paul
authors.initials: P
authors.lastname: Gustafson
authors.forename: Nicola
authors.initials: N
authors.lastname: Cherry
authors.forename: Igor
authors.initials: I
authors.lastname: Burstyn
mesh_terms: D000485:Allergens / Q000276:immunology; D001249:Asthma / Q000139:chemically induced; D001499:Bayes Theorem; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical; D016273:Occupational Exposure
chemical_list: D000485:Allergens