Trim and Fill¶
Duval, S., & Tweedie, R. (2000). Trim and Fill: A Simple Funnel-Plot-Based Method of Testing and Adjusting for Publication Bias in Meta-Analysis. Biometrics, 56(2), 455-463.
Cited by¶
2 citations across 2 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Silence as Signal
- The formal corrections built for meta-analysis — funnel plots, selection-model methods, trim-and-fill — transfer to adverse-event databases with the same structural assumption (recording probability depends on the unobserved true count) and the same catalogue (correct for the gradient, or move to active surveillance).
This sourceFunnel-plot and trim-and-fill corrections that detect and partially undo publication-bias-induced missingness.
Supported in partVerified against the publisher's abstract
Supplies trim-and-fill as a rank-based funnel-plot correction for publication bias, demonstrated on meta-analyses of clinical trials and psychometrics — not on adverse-event databases.
“These are simple rank‐based data augmentation techniques, which formalize the use of funnel plots. ... We illustrate the trim and fill method on existing meta‐analyses of studies in clinical trials and psychometrics.”
- The formal corrections built for meta-analysis — funnel plots, selection-model methods, trim-and-fill — transfer to adverse-event databases with the same structural assumption (recording probability depends on the unobserved true count) and the same catalogue (correct for the gradient, or move to active surveillance).
- Unreliable Narrator
- The Inversion is the correction — funnel-plot asymmetry tests, trim-and-fill, and selection-model estimators take the observed (distorted) distribution of effect sizes and reconstruct an estimate of the underlying effect.
This sourceProvides the trim-and-fill inversion that reconstructs an estimate of the underlying effect from the distorted distribution of published effect sizes.
Supported in partVerified against the publisher's abstract
The paper's abstract states trim-and-fill adjusts for missing studies so the pooled effect estimate recovers, supporting only the trim-and-fill third of the sentence, not funnel-plot tests or selection-model estimators.
“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”
- The Inversion is the correction — funnel-plot asymmetry tests, trim-and-fill, and selection-model estimators take the observed (distorted) distribution of effect sizes and reconstruct an estimate of the underlying effect.
Verification¶
Does it exist? Confirmed. This work's DOI resolves to a registered record, which fixes its identity. That is all it fixes.
Does it back the claim? Read against the text for 2 of 2 citations: 2 supported in part. Each verdict is shown under its citation below, with what in the work backs the sentence.
Support is checked per citation rather than per work — the same source can be cited soundly in one article and wrongly in another. Per-citation recording began recently, so a citation with no recorded check is a gap in the record rather than evidence it went unchecked.
See how references were verified.
Registry ID ref:08b3377fb443 · see in the full table