Meta-evaluation of meta-analysis: ten appraisal questions for biologists

Nakagawa, Shinichi; Noble, Daniel W. A.; Senior, Alistair M.; Lagisz, Malgorzata

doi:10.1186/s12915-017-0357-7

Cited by 579Meta-analysis and systematic reviewsscientometrics and bibliometrics researchPsychology Research and Bibliometrics

Meta-evaluation of meta-analysis: ten appraisal questions for biologists

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Nakagawa, Shinichi, Noble, Daniel W. A., Senior, Alistair M., Lagisz, Malgorzata·2017·BMC Biology

DOI 10.1186/s12915-017-0357-7PMC PMC5336618

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Abstract

Meta-analysis is a statistical procedure for analyzing the combined data from different studies, and can be a major source of concise up-to-date information. The overall conclusions of a meta-analysis, however, depend heavily on the quality of the meta-analytic process, and an appropriate evaluation of the quality of meta-analysis (meta-evaluation) can be challenging. We outline ten questions biologists can ask to critically appraise a meta-analysis. These questions could also act as simple and accessible guidelines for the authors of meta-analyses. We focus on meta-analyses using non-human species, which we term 'biological' meta-analysis. Our ten questions are aimed at enabling a biologist to evaluate whether a biological meta-analysis embodies 'mega-enlightenment', a 'mega-mistake', or something in between.

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Poorly and inexpertly conducted meta-analyses can provide biased and misleading results.
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From Meta-analysis and the science of research synthesis (2018) · cites this paper as [15]

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“This bias, known as publication bias, can be mitigated by gathering the most comprehensive database possible (Lortie et al., 2007; Nakagawa et al., 2017).”
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Authors: Nakagawa, S., Noble, D. W. A., Senior, A. M., & Lagisz, M.
Affiliations: Garvan Institute of Medical Research (AU)
UNSW Sydney (AU)
The University of Sydney (AU)
Corresponding author: Nakagawa, Shinichi
ORCID: Nakagawa, Shinichi
Noble, Daniel W. A.
Senior, Alistair M.
Lagisz, Malgorzata
Venue: BMC Biology
Publisher: Springer Science and Business Media LLC
Published: 2017-03-03
Volume: 15
Issue: 1
Pages: 18-18
ISSN: 1741-7007 (ISSN-L)
DOI: 10.1186/s12915-017-0357-7
PMC: PMC5336618
OpenAlex: W2593372779
Cited by: 579
References: 111
Citations by year: 2026: 84 · 2025: 74 · 2024: 71 · 2023: 66 · 2022: 77 · 2021: 50 · 2020: 64 · 2019: 44 · 2018: 37 · 2017: 12
FWCI: 10.65
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
Locations: BMC Biology (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
UNSWorks (University of New South Wales, Sydney, Australia) (submittedVersion, cc-by-nc-nd)
Funders: University of New South Wales
University of Sydney
Australian Research Council (DE150101774, FT130100268)
Topics: Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
Keywords: meta-evaluation, meta-analysis quality, critical appraisal, non-human species
MeSH terms: Documentation, Humans, Models, Theoretical, Publications, Meta-Analysis as Topic, Publication Bias, Knowledge

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