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ESTIMATING PREVALENCE FROM THE RESULTS OF A SCREENING TEST
Abstract
This paper deals with some basis properties of screening tests. Such tests purport to separate people with disease from people without. Minimal criteria for such a process to be a test are discussed. Various ways of judging the goodness of a test are examined. A common use of tests is to estimate prevalence of disease; frequency of positive tests is shown to be a bad estimate, and the necessary adjustmants are given.
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“Similarity is scored by an LLM judge (GPT-5.4;92.7% binary accuracy, sensitivity 87.1%, specificity 96.8%) and rates are Rogan-Gladen-corrected [Rogan and Gladen, 1978] within stratum, computed per paper, and reported with 95% cluster-bootstrap CIs (10,000 paper-level resamples).”
From On the limits and opportunities of AI reviewers: Reviewing the reviews of Nature-family papers with 45 expert scientists (2026) · cites this paper as Rogan and Gladen, 1978
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McNamara, P. E., Liu, X., & Miller, G. Y. (2003) · RePEc: Research Papers in Economics · doi:10.22004/ag.econ.22023 · Cited by 5
Metadata
- Authors
- ROGAN, W. J., & GLADEN, B.
- Affiliations
- National Institute of Environmental Health Sciences (US)
- Corresponding author
- ROGAN, WALTER J.
- ORCID
- ROGAN, WALTER J.
- Venue
- American Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 1978-01
- Volume
- 107
- Issue
- 1
- Pages
- 71-76
- ISSN
- 0002-9262 (ISSN-L)
- 1476-6256
- OpenAlex
- W2271596670
- Cited by
- 1,001
- References
- 0
- Citations by year
- 2026: 73 · 2025: 45 · 2024: 53 · 2023: 52 · 2022: 72 · 2021: 95 · 2020: 59 · 2019: 43 · 2018: 50 · 2017: 33 · 2016: 27 · 2015: 33 · 2014: 30 · 2013: 28 · 2012: 35
- FWCI
- 4.41
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- screening test, disease prevalence estimation, diagnostic accuracy, positive predictive value, false positive rate
- MeSH terms
- Epidemiologic Methods, Female, Humans, Mass Screening, Morbidity, Population Surveillance
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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