Meta-analysis of a very low proportion through adjusted wald confidence intervals
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10773/27714 |
Resumo: | In this paper we will discuss the meta-analysis of one low proportion. It is well known, that there are several methods to perform the meta-analysis of one proportion, based on a linear combination of proportions or transformed proportions. However, in the context of a linear combination of binomial proportions has been proposed some approximate estimators with some improvements on low proportion estimation. In this paper we will show, with a simple adaptation, the possible contribution of several approximate adjusted Wald confidence intervals (CIs) for the meta-analysis of proportions. In the context of low proportions, a simulation study scenario is carried out to compare these CIs amongst themselves and with other available methods with respect to bias and coverage probabilities, using the fixed effect or the random-effects model. Pointing our interest in rare events (analogous for the abundant events) and taking into account the prevalence estimation of the Methicillin-resistant Staphylococcus aureus with mecc gene, we discuss the choice of the meta-analysis methods on this low proportion. The default meta-analysis methods of meta-analysis software programs are not always the best choice, in particular to the meta-analysis of one low proportion, where the methods including the adjusted Wald can outperform. |
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Meta-analysis of a very low proportion through adjusted wald confidence intervalsMeta-analysisProportionAdjusted wald confidence intervalsLinear combination of binomial proportionsIn this paper we will discuss the meta-analysis of one low proportion. It is well known, that there are several methods to perform the meta-analysis of one proportion, based on a linear combination of proportions or transformed proportions. However, in the context of a linear combination of binomial proportions has been proposed some approximate estimators with some improvements on low proportion estimation. In this paper we will show, with a simple adaptation, the possible contribution of several approximate adjusted Wald confidence intervals (CIs) for the meta-analysis of proportions. In the context of low proportions, a simulation study scenario is carried out to compare these CIs amongst themselves and with other available methods with respect to bias and coverage probabilities, using the fixed effect or the random-effects model. Pointing our interest in rare events (analogous for the abundant events) and taking into account the prevalence estimation of the Methicillin-resistant Staphylococcus aureus with mecc gene, we discuss the choice of the meta-analysis methods on this low proportion. The default meta-analysis methods of meta-analysis software programs are not always the best choice, in particular to the meta-analysis of one low proportion, where the methods including the adjusted Wald can outperform.Crimson Publishers2020-02-28T16:10:06Z2019-07-03T00:00:00Z2019-07-03info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/27714eng2578-024710.31031/OABB.2019.02.000545Afreixo, V.Cruz, S.Freitas, A.Hernandez, M. A.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-22T11:53:42Zoai:ria.ua.pt:10773/27714Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:00:25.585629Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Meta-analysis of a very low proportion through adjusted wald confidence intervals |
title |
Meta-analysis of a very low proportion through adjusted wald confidence intervals |
spellingShingle |
Meta-analysis of a very low proportion through adjusted wald confidence intervals Afreixo, V. Meta-analysis Proportion Adjusted wald confidence intervals Linear combination of binomial proportions |
title_short |
Meta-analysis of a very low proportion through adjusted wald confidence intervals |
title_full |
Meta-analysis of a very low proportion through adjusted wald confidence intervals |
title_fullStr |
Meta-analysis of a very low proportion through adjusted wald confidence intervals |
title_full_unstemmed |
Meta-analysis of a very low proportion through adjusted wald confidence intervals |
title_sort |
Meta-analysis of a very low proportion through adjusted wald confidence intervals |
author |
Afreixo, V. |
author_facet |
Afreixo, V. Cruz, S. Freitas, A. Hernandez, M. A. |
author_role |
author |
author2 |
Cruz, S. Freitas, A. Hernandez, M. A. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Afreixo, V. Cruz, S. Freitas, A. Hernandez, M. A. |
dc.subject.por.fl_str_mv |
Meta-analysis Proportion Adjusted wald confidence intervals Linear combination of binomial proportions |
topic |
Meta-analysis Proportion Adjusted wald confidence intervals Linear combination of binomial proportions |
description |
In this paper we will discuss the meta-analysis of one low proportion. It is well known, that there are several methods to perform the meta-analysis of one proportion, based on a linear combination of proportions or transformed proportions. However, in the context of a linear combination of binomial proportions has been proposed some approximate estimators with some improvements on low proportion estimation. In this paper we will show, with a simple adaptation, the possible contribution of several approximate adjusted Wald confidence intervals (CIs) for the meta-analysis of proportions. In the context of low proportions, a simulation study scenario is carried out to compare these CIs amongst themselves and with other available methods with respect to bias and coverage probabilities, using the fixed effect or the random-effects model. Pointing our interest in rare events (analogous for the abundant events) and taking into account the prevalence estimation of the Methicillin-resistant Staphylococcus aureus with mecc gene, we discuss the choice of the meta-analysis methods on this low proportion. The default meta-analysis methods of meta-analysis software programs are not always the best choice, in particular to the meta-analysis of one low proportion, where the methods including the adjusted Wald can outperform. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-07-03T00:00:00Z 2019-07-03 2020-02-28T16:10:06Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10773/27714 |
url |
http://hdl.handle.net/10773/27714 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2578-0247 10.31031/OABB.2019.02.000545 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Crimson Publishers |
publisher.none.fl_str_mv |
Crimson Publishers |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799137659493285888 |