Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials

Sterne, J. A. C., Sutton, A. J., Ioannidis, J. P. A., Terrin, N., Jones, D. R., Lau, J., Carpenter, J., et al. (2011). Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ.

Type

Journal article

Intellectual base

Primary research

Year

2011

DOI

10.1136/bmj.d4002

Link

https://doi.org/10.1136/bmj.d4002

Cited by

2 citations across 2 artifacts.

Each citation links to the sentence it supports in the citing article.

Domain-specific

• Funnel Plot Asymmetry
  • Statistical formalizations — Egger's regression of the standardized effect on precision, Begg's rank correlation, the trim-and-fill estimator of the missing studies — operationalize the visual pattern as a testable quantity.

    This sourceReviews the statistics that formalise funnel plot asymmetry — Egger's regression of standardised effect on precision, Begg's rank correlation test, and trim and fill among the adjustment methods — and sets out in Box 1 the rival causes (reporting bias, poor methodological quality, true heterogeneity, artefact, chance) an asymmetric plot leaves open; the paper's own emphasis falls on regression-based tests, with the rank-correlation test and trim and fill treated as secondary.

• Publication Bias
  • Genuine heterogeneity, quality differences, analytic choices, and chance can create the same observable

    This sourceThe consensus statement that funnel plot asymmetry must not be equated with publication bias, enumerating true heterogeneity, methodological quality, effect-measure and model choices, and chance among its other causes.

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