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

Thumbnail
Autore
Hartnack S., Eusebi P., Kostoulas P.
Data
2021
Language
en
DOI
10.1002/jmv.26405
Soggetto
immunoglobulin G
immunoglobulin M
Bayesian latent class model
coronavirus disease 2019
diagnostic test
diagnostic test accuracy study
gold standard
human
Letter
Markov chain Monte Carlo method
mathematical model
prevalence
probability
reverse transcription polymerase chain reaction
sensitivity and specificity
validity
Bayes theorem
latent class analysis
standard
statistical model
Bayes Theorem
COVID-19
Diagnostic Tests, Routine
Humans
Latent Class Analysis
Models, Statistical
Reference Standards
Reverse Transcriptase Polymerase Chain Reaction
SARS-CoV-2
Sensitivity and Specificity
John Wiley and Sons Inc
Mostra tutti i dati dell'item
Abstract
[No abstract available]
URI
http://hdl.handle.net/11615/73914
Collections
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ. [19735]

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