Journal article
Bayesian analysis of a matched case-control study with expert prior information on both the misclassification of exposure and the exposure-disease association
Statistics in medicine, v 28(27), pp 3411-3423
30 Nov 2009
PMID: 19691019
Featured in Collection : UN Sustainable Development Goals @ Drexel
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. Copyright (C) 2009 John Wiley & Sons, Ltd.
Metrics
Details
- Title
- Bayesian analysis of a matched case-control study with expert prior information on both the misclassification of exposure and the exposure-disease association
- Creators
- Juxin Liu - Univ Saskatchewan, Dept Math & Stat, Saskatoon, SK S7N 5E6, CanadaPaul Gustafson - University of SaskatchewanNicola Cherry - University of AlbertaIgor Burstyn - University of Alberta
- Publication Details
- Statistics in medicine, v 28(27), pp 3411-3423
- Publisher
- Wiley
- Number of pages
- 13
- Grant note
- Natural Sciences and Engineering Research Council of Canada; Natural Sciences and Engineering Research Council of Canada (NSERC); CGIAR Alberta Heritage Foundation for Medical Research; General Electric AllerGen NCE Inc 62863 / Canadian Institutes of Health Research; Canadian Institutes of Health Research (CIHR)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Environmental and Occupational Health
- Web of Science ID
- WOS:000272090000005
- Scopus ID
- 2-s2.0-70350223200
- Other Identifier
- 991019203329804721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Mathematical & Computational Biology
- Medical Informatics
- Medicine, Research & Experimental
- Public, Environmental & Occupational Health
- Statistics & Probability