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Cited by 373Meta-analysis and systematic reviewsStatistical Methods in Epidemiologyscientometrics and bibliometrics research

Assessment of regression-based methods to adjust for publication bias through a comprehensive simulation study

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Moreno, Santiago G, Sutton, Alex J, Ades, AE, Stanley, Tom D, Abrams, Keith R, Peters, Jaime L, Cooper, Nicola J·2009·BMC Medical Research Methodology
DOI 10.1186/1471-2288-9-2PMC PMC2649158
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Abstract

BACKGROUND: In meta-analysis, the presence of funnel plot asymmetry is attributed to publication or other small-study effects, which causes larger effects to be observed in the smaller studies. This issue potentially mean inappropriate conclusions are drawn from a meta-analysis. If meta-analysis is to be used to inform decision-making, a reliable way to adjust pooled estimates for potential funnel plot asymmetry is required. METHODS: A comprehensive simulation study is presented to assess the performance of different adjustment methods including the novel application of several regression-based methods (which are commonly applied to detect publication bias rather than adjust for it) and the popular Trim & Fill algorithm. Meta-analyses with binary outcomes, analysed on the log odds ratio scale, were simulated by considering scenarios with and without i) publication bias and; ii) heterogeneity. Publication bias was induced through two underlying mechanisms assuming the probability of publication depends on i) the study effect size; or ii) the p-value. RESULTS: The performance of all methods tended to worsen as unexplained heterogeneity increased and the number of studies in the meta-analysis decreased. Applying the methods conditional on an initial test for the presence of funnel plot asymmetry generally provided poorer performance than the unconditional use of the adjustment method. Several of the regression based methods consistently outperformed the Trim & Fill estimators. CONCLUSION: Regression-based adjustments for publication bias and other small study effects are easy to conduct and outperformed more established methods over a wide range of simulation scenarios.

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  • P-curve and variations of Egger's regression have been found to perform better than the trim-and-fill method for detecting publication bias.

    “However, more novel and promising methods, such as p-curve (Simonsohn, Nelson, & Simmons, 2014) and variations of Egger's regression (Egger, Smith, Schneider, & Minder, 1997;Moreno et al., 2009), have been found to perform better than the trim and fill method.”

    From Working memory training revisited: A multi-level meta-analysis of n-back training studies (2017) · cites this paper as Moreno et al., 2009

    The Abstract (Methods and Results) says several regression-based methods outperformed Trim & Fill, and the Conclusion identifies an Egger variant among the promising methods. But the comparison concerns adjustment for publication bias, not performance in detecting it. The sentence cites Simonsohn et al., rather than Moreno et al., for p-curve. (LLM, conf=0.88)

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  • Bias adjustments can improve performance relative to a meta-analysis that does not adjust for publication bias.

    “Bias adjustments can improve performance relative to a meta-analysis that does not adjust for publication bias (Carter et al., 2019; McShane et al., 2016; Moreno et al., 2009; Simonsohn et al., 2014).”

    From Do Salient Social Norms Moderate Mortality Salience Effects? A (Challenging) Meta-Analysis of Terror Management Studies (2023) · cites this paper as Moreno et al., 2009

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Authors
Moreno, S. G., Sutton, A. J., Ades, A., Stanley, T. D., Abrams, K. R., Peters, J. L., & Cooper, N. J.
Affiliations
  • University of Leicester (GB)
  • Hendrix College (US)
Corresponding author
Moreno, Santiago G
ORCID
Venue
BMC Medical Research Methodology
Publisher
Springer Science and Business Media LLC
Published
2009-01-12
Volume
9
Issue
1
Pages
2-2
ISSN
1471-2288 (ISSN-L)
DOI
10.1186/1471-2288-9-2
PMC
PMC2649158
OpenAlex
W1970128129
Cited by
373
References
44
Citations by year
2026: 9 · 2025: 11 · 2024: 11 · 2023: 11 · 2022: 31 · 2021: 28 · 2020: 26 · 2019: 21 · 2018: 39 · 2017: 31 · 2016: 18 · 2015: 26 · 2014: 24 · 2013: 26 · 2012: 19
FWCI
24.04
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Medical Research Methodology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • Own your potential (DEAKIN) (submittedVersion)
  • Figshare (submittedVersion, cc-by)
  • Leicester Research Archive (University of Leicester) (submittedVersion, cc-by)
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 › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
Keywords
publication bias, small-study effects, trim and fill, funnel plot asymmetry, meta-analysis, heterogeneity, binary outcomes, odds ratio, simulation study
MeSH terms
Computer Simulation, Humans, Regression Analysis, Meta-Analysis as Topic, Odds Ratio, Randomized Controlled Trials as Topic, Publication Bias

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