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...
- Autores:
- Tipo de recurso:
- 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
- Rights
- License
- Abierto (Texto Completo)
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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 |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.spa.spa.fl_str_mv |
Artículo |
dc.identifier.issn.none.fl_str_mv |
1201751 |
dc.identifier.uri.none.fl_str_mv |
https://repository.urosario.edu.co/handle/10336/23012 |
identifier_str_mv |
1201751 |
url |
https://repository.urosario.edu.co/handle/10336/23012 |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
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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https://www.scopus.com/inward/record.uri?eid=2-s2.0-84871630067&partnerID=40&md5=49b08947305086481b9536f21ac6ed0e |
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http://purl.org/coar/access_right/c_abf2 |
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Abierto (Texto Completo) |
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Abierto (Texto Completo) http://purl.org/coar/access_right/c_abf2 |
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application/pdf |
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Universidad del Rosario |
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reponame:Repositorio Institucional EdocUR |
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