Contour–enhanced funnel plots for meta–analysis
Tom M. Palmer
Department of Health Sciences
University of Leicester, UK
tmp8@le.ac.uk
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Jaime L. Peters
School of Mathematical Sciences
Queensland University of Technology
Brisbane, Australia
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Alex J. Sutton
Department of Health Sciences
University of Leicester, UK
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Santiago G. Moreno
Department of Health Sciences
University of Leicester, UK
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Abstract. Funnel plots are commonly used to investigate publication and related biases
in meta-analysis. Although asymmetry in the appearance of a funnel plot is
often interpreted as being caused by publication bias, in reality the
asymmetry could be due to other factors that cause systematic differences in
the results of large and small studies, for example, confounding factors
such as differential study quality. Funnel plots can be enhanced by adding
contours of statistical significance to aid in interpreting the funnel plot.
If studies appear to be missing in areas of low statistical significance,
then it is possible that the asymmetry is due to publication bias. If
studies appear to be missing in areas of high statistical significance, then
publication bias is a less likely cause of the funnel asymmetry. It is
proposed that this enhancement to funnel plots should be used routinely for
meta-analyses where it is possible that results could be suppressed on the
basis of their statistical significance.
View all articles by these authors:
Tom M. Palmer, Jaime L. Peters, Alex J. Sutton, Santiago G. Moreno
View all articles with these keywords:
confunnel, funnel plots, meta-analysis, publication bias, small-study effects
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