Journal article
The Rogan-Gladen estimator for outcome misclassification
- Abstract:
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Outcome measurement error is common in epidemiologic studies and often leads to bias in estimates of prevalences, risks, and their contrasts. The Rogan-Gladen estimator (1) provides an elegant solution to account for misclassification of a binary outcome when estimating risk or prevalence, which, in turn, can be used to produce valid estimates of contrasts in these measures. Here, we review the Rogan-Gladen estimator, provide intuition for its properties, and briefly illustrate how it can be combined with approaches to account for other sources of bias.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 459.7KB, Terms of use)
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(Preview, Supplementary materials, pdf, 568.4KB, Terms of use)
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- Publisher copy:
- 10.1093/aje/kwag057
Authors
- Publisher:
- Oxford University Press
- Journal:
- American Journal of Epidemiology More from this journal
- Article number:
- kwag057
- Publication date:
- 2026-03-30
- Acceptance date:
- 2026-03-05
- DOI:
- EISSN:
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1476-6256
- ISSN:
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0002-9262
- Language:
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English
- Pubs id:
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2388649
- Local pid:
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pubs:2388649
- Deposit date:
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2026-03-12
- ARK identifier:
Terms of use
- Copyright holder:
- Edwards et al
- Copyright date:
- 2026
- Rights statement:
- © The Author(s) 2026. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved.
- Notes:
- The author accepted manuscript (AAM) of this paper has been made available under the University of Oxford's Open Access Publications Policy, and a CC BY public copyright licence has been applied.
- Licence:
- CC Attribution (CC BY)
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