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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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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. |
format | Online Article Text |
id | pubmed-10138056 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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