Article ; Online: A Note on Cherry-Picking in Meta-Analyses.
2023 Volume 25, Issue 4
Abstract: 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 ... ...
Abstract | 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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Language | English |
Publishing date | 2023-04-19 |
Publishing country | Switzerland |
Document type | Journal Article |
ZDB-ID | 2014734-X |
ISSN | 1099-4300 ; 1099-4300 |
ISSN (online) | 1099-4300 |
ISSN | 1099-4300 |
DOI | 10.3390/e25040691 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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