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152230 - Standardized mean differences.pdf (2.77 MB)

Standardized mean differences cause funnel plot distortion in publication bias assessments

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posted on 2023-05-21, 11:45 authored by Zwetsloot, PP, Van Der Naald, M, Sena, ES, David Howells, IntHout, J, De Groot, JAH, Chamuleau, SAJ, MacLeod, MR, Wever, KE
Meta-analyses are increasingly used for synthesis of evidence from biomedical research, and often include an assessment of publication bias based on visual or analytical detection of asymmetry in funnel plots. We studied the influence of different normalisation approaches, sample size and intervention effects on funnel plot asymmetry, using empirical datasets and illustrative simulations. We found that funnel plots of the Standardized Mean Difference (SMD) plotted against the standard error (SE) are susceptible to distortion, leading to overestimation of the existence and extent of publication bias. Distortion was more severe when the primary studies had a small sample size and when an intervention effect was present. We show that using the Normalised Mean Difference measure as effect size (when possible), or plotting the SMD against a sample size-based precision estimate, are more reliable alternatives. We conclude that funnel plots using the SMD in combination with the SE are unsuitable for publication bias assessments and can lead to false-positive results.

History

Publication title

eLife

Volume

6

Article number

e24260

Number

e24260

Pagination

1-20

ISSN

2050-084X

Department/School

Tasmanian School of Medicine

Publisher

eLife Sciences Publications Ltd

Place of publication

United Kingdom

Rights statement

Copyright 2017 Bradshaw et al. This article is distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License, (https://creativecommons.org/licenses/by/4.0/) which permits unrestricted use and redistribution provided that the original author and source are credited.

Repository Status

  • Open

Socio-economic Objectives

Diagnosis of human diseases and conditions; Expanding knowledge in the biological sciences

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