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Assessing publication bias in meta‐analyses in the presence of between‐study heterogeneity

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  • Jaime L. Peters
  • Alex J. Sutton
  • David R. Jones
  • Keith R. Abrams
  • Lesley Rushton
  • Santiago G. Moreno

Abstract

Summary. Between‐study heterogeneity and publication bias are common features of a meta‐analysis that can be present simultaneously. When both are suspected, consideration must be made of each in the assessment of the other. We consider extended funnel plot tests for detecting publication bias, and selection modelling and trim‐and‐fill methods to adjust for publication bias in the presence of between‐study heterogeneity. These methods are applied to two example data sets. Results indicate that ignoring between‐study heterogeneity when assessing publication bias can be misleading, but that methods to test or adjust for publication bias in the presence of heterogeneity may not be powerful when the meta‐analysis is not large. It is therefore unrealistic to expect to disentangle the effects of publication bias and heterogeneity reliably in all except the largest meta‐analyses.

Suggested Citation

  • Jaime L. Peters & Alex J. Sutton & David R. Jones & Keith R. Abrams & Lesley Rushton & Santiago G. Moreno, 2010. "Assessing publication bias in meta‐analyses in the presence of between‐study heterogeneity," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(3), pages 575-591, July.
    • Handle: RePEc:bla:jorssa:v:173:y:2010:i:3:p:575-591
    DOI: 10.1111/j.1467-985X.2009.00629.x
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    References listed on IDEAS

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    1. J. Copas, 1999. "What works?: selectivity models and meta‐analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(1), pages 95-109.
    2. Sue Duval & Richard Tweedie, 2000. "Trim and Fill: A Simple Funnel-Plot–Based Method of Testing and Adjusting for Publication Bias in Meta-Analysis," Biometrics, The International Biometric Society, vol. 56(2), pages 455-463, June.
    3. Larry V. Hedges & Jack L. Vevea, 1996. "Estimating Effect Size Under Publication Bias: Small Sample Properties and Robustness of a Random Effects Selection Model," Journal of Educational and Behavioral Statistics, , vol. 21(4), pages 299-332, December.
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    1. Polák, Petr, 2017. "The productivity paradox: A meta-analysis," Information Economics and Policy, Elsevier, vol. 38(C), pages 38-54.
    2. Dan Jackson, 2018. "Discussion on Quantifying publication bias in meta‐analysis," Biometrics, The International Biometric Society, vol. 74(3), pages 795-796, September.
    3. Sergio Nolazco & Kaspar Delhey & Shinichi Nakagawa & Anne Peters, 2022. "Ornaments are equally informative in male and female birds," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    4. Celbis, Mehmet Güney & Nijkamp, Peter & Poot, Jacques, 2013. "How big is the impact of infrastructure on trade? Evidence from meta-analysis," MERIT Working Papers 2013-032, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    5. Augusteijn, Hilde & van Aert, Robbie Cornelis Maria & van Assen, Marcel A. L. M., 2017. "The Effect of Publication Bias on the Assessment of Heterogeneity," OSF Preprints gv25c, Center for Open Science.
    6. Anna Chaimani & Julian P T Higgins & Dimitris Mavridis & Panagiota Spyridonos & Georgia Salanti, 2013. "Graphical Tools for Network Meta-Analysis in STATA," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-12, October.

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