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Standardized mean differences cause funnel plot distortion in publication bias assessments
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 interventi...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5621838/ https://www.ncbi.nlm.nih.gov/pubmed/28884685 http://dx.doi.org/10.7554/eLife.24260 |
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author | Zwetsloot, Peter-Paul Van Der Naald, Mira Sena, Emily S Howells, David W IntHout, Joanna De Groot, Joris AH Chamuleau, Steven AJ MacLeod, Malcolm R Wever, Kimberley E |
author_facet | Zwetsloot, Peter-Paul Van Der Naald, Mira Sena, Emily S Howells, David W IntHout, Joanna De Groot, Joris AH Chamuleau, Steven AJ MacLeod, Malcolm R Wever, Kimberley E |
author_sort | Zwetsloot, Peter-Paul |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5621838 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-56218382017-10-02 Standardized mean differences cause funnel plot distortion in publication bias assessments Zwetsloot, Peter-Paul Van Der Naald, Mira Sena, Emily S Howells, David W IntHout, Joanna De Groot, Joris AH Chamuleau, Steven AJ MacLeod, Malcolm R Wever, Kimberley E eLife Epidemiology and Global Health 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. eLife Sciences Publications, Ltd 2017-09-08 /pmc/articles/PMC5621838/ /pubmed/28884685 http://dx.doi.org/10.7554/eLife.24260 Text en © 2017, Zwetsloot et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Epidemiology and Global Health Zwetsloot, Peter-Paul Van Der Naald, Mira Sena, Emily S Howells, David W IntHout, Joanna De Groot, Joris AH Chamuleau, Steven AJ MacLeod, Malcolm R Wever, Kimberley E Standardized mean differences cause funnel plot distortion in publication bias assessments |
title | Standardized mean differences cause funnel plot distortion in publication bias assessments |
title_full | Standardized mean differences cause funnel plot distortion in publication bias assessments |
title_fullStr | Standardized mean differences cause funnel plot distortion in publication bias assessments |
title_full_unstemmed | Standardized mean differences cause funnel plot distortion in publication bias assessments |
title_short | Standardized mean differences cause funnel plot distortion in publication bias assessments |
title_sort | standardized mean differences cause funnel plot distortion in publication bias assessments |
topic | Epidemiology and Global Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5621838/ https://www.ncbi.nlm.nih.gov/pubmed/28884685 http://dx.doi.org/10.7554/eLife.24260 |
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