Two dependent diagnostic tests: Use of copula functions in the estimation of the prevalence and performance test parameters

In this paper, we introduce a Bayesian analysis to estimate the prevalence and performance test parameters of two diagnostic tests. We concentrated our interest in studies where the individuals with negative outcomes in both tests are not verified by a gold standard. Given that the screening tests a...

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Fecha de publicación:
2012
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/23012
Acceso en línea:
https://repository.urosario.edu.co/handle/10336/23012
Palabra clave:
Bayes analysis
Copula
Dependence
Monte carlo simulation
Public health
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spelling 15476e54-65c7-4aa0-b74a-68d7462e83ad-11748df6d-ea90-4efc-8d82-a634ca1cb2b1-12020-05-25T23:59:15Z2020-05-25T23:59:15Z2012In this paper, we introduce a Bayesian analysis to estimate the prevalence and performance test parameters of two diagnostic tests. We concentrated our interest in studies where the individuals with negative outcomes in both tests are not verified by a gold standard. Given that the screening tests are applied in the same individual we assume dependence between test results. Generally, to capture the possible existing dependence between test outcomes, it is assumed a binary covariance structure, but in this paper, as an alternative for this modeling, we consider the use of copula function structures. The posterior summaries of interest are obtained using standard MCMC (Markov Chain Monte Carlo) methods. We compare the results obtained with our approach with those obtained using binary covariance and assuming independence. We considerate two published medical data sets to illustrate the approach.application/pdf1201751https://repository.urosario.edu.co/handle/10336/23012eng347No. 3331Revista Colombiana de EstadisticaVol. 35Revista Colombiana de Estadistica, ISSN:1201751, Vol.35, No.3 (2012); pp. 331-347https://www.scopus.com/inward/record.uri?eid=2-s2.0-84871630067&partnerID=40&md5=49b08947305086481b9536f21ac6ed0eAbierto (Texto Completo)http://purl.org/coar/access_right/c_abf2instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURBayes analysisCopulaDependenceMonte carlo simulationPublic healthTwo dependent diagnostic tests: Use of copula functions in the estimation of the prevalence and performance test parametersDos pruebas para diagnóstico clínico: Uso de funciones copula en la estimación de la prevalencia y los parámetros de desempeño de las pruebasarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Tovar J.R.Achcar J.A.ORIGINAL36871-223642-1-PB.pdfapplication/pdf615719https://repository.urosario.edu.co/bitstreams/0f5908c6-5e41-483c-9b37-e8cd7254aef8/download2de971f195ae63c11c0b6d3356715b78MD51TEXT36871-223642-1-PB.pdf.txt36871-223642-1-PB.pdf.txtExtracted texttext/plain45171https://repository.urosario.edu.co/bitstreams/ee74a763-e7b9-4ff9-9055-cdb6b8ad70d6/downloade20a9596b7a05e1f789bc4d957068d7dMD52THUMBNAIL36871-223642-1-PB.pdf.jpg36871-223642-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg2976https://repository.urosario.edu.co/bitstreams/07e103ba-db62-4396-85e2-28c0836aa918/downloade626c7c0a00b93c06ec74e18e764beecMD5310336/23012oai:repository.urosario.edu.co:10336/230122022-05-02 07:37:20.856778https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co
dc.title.spa.fl_str_mv Two dependent diagnostic tests: Use of copula functions in the estimation of the prevalence and performance test parameters
dc.title.TranslatedTitle.spa.fl_str_mv Dos pruebas para diagnóstico clínico: Uso de funciones copula en la estimación de la prevalencia y los parámetros de desempeño de las pruebas
title Two dependent diagnostic tests: Use of copula functions in the estimation of the prevalence and performance test parameters
spellingShingle Two dependent diagnostic tests: Use of copula functions in the estimation of the prevalence and performance test parameters
Bayes analysis
Copula
Dependence
Monte carlo simulation
Public health
title_short Two dependent diagnostic tests: Use of copula functions in the estimation of the prevalence and performance test parameters
title_full Two dependent diagnostic tests: Use of copula functions in the estimation of the prevalence and performance test parameters
title_fullStr Two dependent diagnostic tests: Use of copula functions in the estimation of the prevalence and performance test parameters
title_full_unstemmed Two dependent diagnostic tests: Use of copula functions in the estimation of the prevalence and performance test parameters
title_sort Two dependent diagnostic tests: Use of copula functions in the estimation of the prevalence and performance test parameters
dc.subject.keyword.spa.fl_str_mv Bayes analysis
Copula
Dependence
Monte carlo simulation
Public health
topic Bayes analysis
Copula
Dependence
Monte carlo simulation
Public health
description In this paper, we introduce a Bayesian analysis to estimate the prevalence and performance test parameters of two diagnostic tests. We concentrated our interest in studies where the individuals with negative outcomes in both tests are not verified by a gold standard. Given that the screening tests are applied in the same individual we assume dependence between test results. Generally, to capture the possible existing dependence between test outcomes, it is assumed a binary covariance structure, but in this paper, as an alternative for this modeling, we consider the use of copula function structures. The posterior summaries of interest are obtained using standard MCMC (Markov Chain Monte Carlo) methods. We compare the results obtained with our approach with those obtained using binary covariance and assuming independence. We considerate two published medical data sets to illustrate the approach.
publishDate 2012
dc.date.created.spa.fl_str_mv 2012
dc.date.accessioned.none.fl_str_mv 2020-05-25T23:59:15Z
dc.date.available.none.fl_str_mv 2020-05-25T23:59:15Z
dc.type.eng.fl_str_mv article
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dc.identifier.issn.none.fl_str_mv 1201751
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dc.relation.citationEndPage.none.fl_str_mv 347
dc.relation.citationIssue.none.fl_str_mv No. 3
dc.relation.citationStartPage.none.fl_str_mv 331
dc.relation.citationTitle.none.fl_str_mv Revista Colombiana de Estadistica
dc.relation.citationVolume.none.fl_str_mv Vol. 35
dc.relation.ispartof.spa.fl_str_mv Revista Colombiana de Estadistica, ISSN:1201751, Vol.35, No.3 (2012); pp. 331-347
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