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pubmed-article:1410959pubmed:abstractTextEpidemiological 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.lld:pubmed
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pubmed-article:1410959pubmed:statusMEDLINElld:pubmed
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pubmed-article:1410959pubmed:issn0277-6715lld:pubmed
pubmed-article:1410959pubmed:authorpubmed-author:RichardsonSSlld:pubmed
pubmed-article:1410959pubmed:authorpubmed-author:GilksW RWRlld:pubmed
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pubmed-article:1410959pubmed:pagination1443-63lld:pubmed
pubmed-article:1410959pubmed:dateRevised2006-11-15lld:pubmed
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pubmed-article:1410959pubmed:year1992lld:pubmed
pubmed-article:1410959pubmed:articleTitleAnalysis of disease risks using ancillary risk factors, with application to job-exposure matrices.lld:pubmed
pubmed-article:1410959pubmed:affiliationMedical Research Council Biostatistics Unit, Fair View Lodge, Cambridge, U.K.lld:pubmed
pubmed-article:1410959pubmed:publicationTypeJournal Articlelld:pubmed
pubmed-article:1410959pubmed:publicationTypeResearch Support, Non-U.S. Gov'tlld:pubmed