Evidence map›Paper›PMID 28257642›Full record

SynthesisBMC biology2017

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

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

Abstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in BMC biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 189 papers, 94 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
189citing papers in PubMed, 94 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

189 citing papers in PubMed, 94 syntheses or guidelines pooled it.

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129 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shinichi NakagawaEvolution & Ecology Research Centre and School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW, 2052, Australia. s.nakagawa@unsw.edu.au.
Daniel W A NobleEvolution & Ecology Research Centre and School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW, 2052, Australia.
Alistair M SeniorCharles Perkins Centre, University of Sydney, Sydney, NSW, 2006, Australia.
Malgorzata LagiszEvolution & Ecology Research Centre and School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW, 2052, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Meta-Analysis as TopicDocumentationHumansKnowledgeModels, TheoreticalPublication BiasPublicationsBiological importanceEffect sizeMeta-regressionMeta-researchNon-independencePublication biasQuantitative synthesisReporting biasStatistical significanceSystematic review

Identifiers

PMID28257642
PMCPMC5336618

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.