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Trim and Fill: A Simple Funnel‐Plot–Based Method of Testing and Adjusting for Publication Bias in Meta‐Analysis

2000/06/01 by Sue Duval, Richard Tweedie, Richard L. Tweedie · 14,108 citations
Computer Science · Decision Sciences · Mathematics · Medicine · #Computer science #Confidence interval #Covariate #Data Analysis with R #Econometrics #Funnel plot #Mathematics #Medicine #Meta-analysis #Meta-analysis and systematic reviews #Missing data #Nonparametric statistics #Point estimation #Publication bias #Sample size determination #Simple (philosophy) #Statistical Methods in Clinical Trials #Statistical hypothesis testing #Statistics #Trim

paper · doi:10.1111/j.0006-341x.2000.00455.x

published in Biometrics 56(2), 455-463 (Oxford University Press)

openalex publication_date 2000/06/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

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.

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