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Bayesian analysis of a matched case–control study with expert prior information on both the misclassification of exposure and the exposure–disease association
Author(s) -
Liu Juxin,
Gustafson Paul,
Cherry Nicola,
Burstyn Igor
Publication year - 2009
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.3694
Subject(s) - dirichlet distribution , multinomial distribution , bayesian probability , statistics , association (psychology) , prior probability , disease , computer science , a priori and a posteriori , econometrics , medicine , mathematics , psychology , mathematical analysis , psychotherapist , boundary value problem , philosophy , epistemology
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. Copyright © 2009 John Wiley & Sons, Ltd.