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A Note on Cherry-Picking in Meta-Analyses

We study selection bias in meta-analyses by assuming the presence of researchers (meta-analysts) who intentionally or unintentionally cherry-pick a subset of studies by defining arbitrary inclusion and/or exclusion criteria that will lead to their desired results. When the number of studies is suffi...

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Detalles Bibliográficos
Autores principales: Yoneoka, Daisuke, Rieck, Bastian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10138056/
https://www.ncbi.nlm.nih.gov/pubmed/37190479
http://dx.doi.org/10.3390/e25040691
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author Yoneoka, Daisuke
Rieck, Bastian
author_facet Yoneoka, Daisuke
Rieck, Bastian
author_sort Yoneoka, Daisuke
collection PubMed
description We study selection bias in meta-analyses by assuming the presence of researchers (meta-analysts) who intentionally or unintentionally cherry-pick a subset of studies by defining arbitrary inclusion and/or exclusion criteria that will lead to their desired results. When the number of studies is sufficiently large, we theoretically show that a meta-analysts might falsely obtain (non)significant overall treatment effects, regardless of the actual effectiveness of a treatment. We analyze all theoretical findings based on extensive simulation experiments and practical clinical examples. Numerical evaluations demonstrate that the standard method for meta-analyses has the potential to be cherry-picked.
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spelling pubmed-101380562023-04-28 A Note on Cherry-Picking in Meta-Analyses Yoneoka, Daisuke Rieck, Bastian Entropy (Basel) Article We study selection bias in meta-analyses by assuming the presence of researchers (meta-analysts) who intentionally or unintentionally cherry-pick a subset of studies by defining arbitrary inclusion and/or exclusion criteria that will lead to their desired results. When the number of studies is sufficiently large, we theoretically show that a meta-analysts might falsely obtain (non)significant overall treatment effects, regardless of the actual effectiveness of a treatment. We analyze all theoretical findings based on extensive simulation experiments and practical clinical examples. Numerical evaluations demonstrate that the standard method for meta-analyses has the potential to be cherry-picked. MDPI 2023-04-19 /pmc/articles/PMC10138056/ /pubmed/37190479 http://dx.doi.org/10.3390/e25040691 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yoneoka, Daisuke
Rieck, Bastian
A Note on Cherry-Picking in Meta-Analyses
title A Note on Cherry-Picking in Meta-Analyses
title_full A Note on Cherry-Picking in Meta-Analyses
title_fullStr A Note on Cherry-Picking in Meta-Analyses
title_full_unstemmed A Note on Cherry-Picking in Meta-Analyses
title_short A Note on Cherry-Picking in Meta-Analyses
title_sort note on cherry-picking in meta-analyses
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10138056/
https://www.ncbi.nlm.nih.gov/pubmed/37190479
http://dx.doi.org/10.3390/e25040691
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