Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis

Sue Duval, Richard Tweedie

Research output: Contribution to journalArticlepeer-review

5838 Scopus citations

Abstract

We study recently developed nonparametric methods for estimating the number of missing studies that might exist in a meta-analysis and the effect that these studies might have had on its outcome. These are simple rank-based data augmentation techniques, which formalize the use of funnel plots. We show that they provide effective and relatively powerful tests for evaluating the existence of such publication bias. After adjusting for missing studies, we find that the point estimate of the overall effect size is approximately correct and coverage of the effect size confidence intervals is substantially improved, in many cases recovering the nominal confidence levels entirely. We illustrate the trim and fill method on existing meta-analyses of studies in clinical trials and psychometrics.

Original languageEnglish (US)
Pages (from-to)455-463
Number of pages9
JournalBiometrics
Volume56
Issue number2
DOIs
StatePublished - Jun 2000

Keywords

  • Data augmentation
  • File drawer problem
  • Funnel plots
  • IQ
  • Malaria
  • Meta- analysis
  • Missing studies
  • Publication bias

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