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Estimation and inference for case-control studies with multiple non-gold standard exposure assessments: with an occupational health application.
- Source :
-
Biostatistics (Oxford, England) [Biostatistics] 2009 Oct; Vol. 10 (4), pp. 591-602. Date of Electronic Publication: 2009 Jun 09. - Publication Year :
- 2009
-
Abstract
- In occupational case-control studies, work-related exposure assessments are often fallible measures of the true underlying exposure. In lieu of a gold standard, often more than 2 imperfect measurements (e.g. triads) are used to assess exposure. While methods exist to assess the diagnostic accuracy in the absence of a gold standard, these methods are infrequently used to correct for measurement error in exposure-disease associations in occupational case-control studies. Here, we present a likelihood-based approach that (a) provides evidence regarding whether the misclassification of tests is differential or nondifferential; (b) provides evidence whether the misclassification of tests is independent or dependent conditional on latent exposure status, and (c) estimates the measurement error-corrected exposure-disease association. These approaches use information from all imperfect assessments simultaneously in a unified manner, which in turn can provide a more accurate estimate of exposure-disease association than that based on individual assessments. The performance of this method is investigated through simulation studies and applied to the National Occupational Hazard Survey, a case-control study assessing the association between asbestos exposure and mesothelioma.
- Subjects :
- Asbestos administration & dosage
Asbestos adverse effects
Case-Control Studies
Confidence Intervals
Data Collection
Humans
Likelihood Functions
Mesothelioma etiology
Models, Statistical
Occupational Exposure standards
Occupational Health statistics & numerical data
United States
Biostatistics methods
Occupational Exposure statistics & numerical data
Subjects
Details
- Language :
- English
- ISSN :
- 1468-4357
- Volume :
- 10
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- Biostatistics (Oxford, England)
- Publication Type :
- Academic Journal
- Accession number :
- 19515637
- Full Text :
- https://doi.org/10.1093/biostatistics/kxp015