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Bayesian latent class models to estimate diagnostic test accuracies of COVID‐19 tests


Hartnack, Sonja; Eusebi, Paolo; Kostoulas, Polychronis (2021). Bayesian latent class models to estimate diagnostic test accuracies of COVID‐19 tests. Journal of Medical Virology, 93(2):639-640.

Abstract

With great interest we read the article from Dramé et al. 1 “Should RT‐PC be considered as gold standard in the diagnosis of Covid‐19” questioning the conclusions from Cassaniti et al.2. We agree with the argument that considering RT‐PCR as gold standard when evaluating a new test will inevitably lead to biased test accuracy estimates of the new test1.

Abstract

With great interest we read the article from Dramé et al. 1 “Should RT‐PC be considered as gold standard in the diagnosis of Covid‐19” questioning the conclusions from Cassaniti et al.2. We agree with the argument that considering RT‐PCR as gold standard when evaluating a new test will inevitably lead to biased test accuracy estimates of the new test1.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:05 Vetsuisse Faculty > Chair in Veterinary Epidemiology
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
Scopus Subject Areas:Life Sciences > Virology
Health Sciences > Infectious Diseases
Uncontrolled Keywords:Virology, Infectious Diseases
Language:English
Date:1 February 2021
Deposited On:02 Sep 2020 19:17
Last Modified:01 Oct 2021 17:34
Publisher:Wiley-Blackwell Publishing, Inc.
ISSN:0146-6615
OA Status:Hybrid
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1002/jmv.26405
PubMed ID:32770741

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