Cited by 503Meta-analysis and systematic reviewsStatistical Methods in Epidemiologyscientometrics and bibliometrics research

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Meta-analysis, funnel plots and sensitivity analysis

Open access

Copas, J.·2000·Biostatistics

DOI 10.1093/biostatistics/1.3.247

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Abstract

Publication bias is a major problem, perhaps the major problem, in meta-analysis (or systematic reviews). Small studies are more likely to be published if their results are 'significant' than if their results are negative or inconclusive, and so the studies available for review are biased in favour of those with positive outcomes. Correcting for this bias is not possible without making untestable assumptions. In this paper, a sensitivity analysis is suggested which is based on fitting a model to the funnel plot. Some examples are discussed.

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Crossref · 10.1093/biostatistics/1.3.247

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Authors: Copas, J.
Affiliations: University of Warwick (GB)
Corresponding author: Copas, J.
ORCID: Copas, J.
Venue: Biostatistics
Publisher: Oxford University Press (OUP)
Published: 2000-09-01
Volume: 1
Issue: 3
Pages: 247-262
ISSN: 1465-4644 (ISSN-L)
1468-4357
DOI: 10.1093/biostatistics/1.3.247
OpenAlex: W2111636520
Cited by: 503
References: 19
Citations by year: 2026: 36 · 2025: 42 · 2024: 32 · 2023: 31 · 2022: 42 · 2021: 42 · 2020: 42 · 2019: 21 · 2018: 19 · 2017: 34 · 2016: 24 · 2015: 23 · 2014: 24 · 2013: 16 · 2012: 12
FWCI: 2.54
Type: journal article
Language: en
Open access: green
doi.org
Locations: Biostatistics (publishedVersion)
PubMed (publishedVersion)
HighWire Press Open Archive (submittedVersion)
Newcastle University ePrints (Newcastle Univesity)
Biometrics
Topics: Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Social Sciences › Library and Information Sciences › scientometrics and bibliometrics research
Keywords: publication bias, funnel plot, sensitivity analysis, meta-analysis, small-study effects, bias correction

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