Statistics in Medicine · 2004 · 819 citations · 21 references
EducationEconomicsCausal InferenceHealth EconomicsInstitutional ResearchCausal Graphical ModelsComparative AnalysisControl ChartsFunnel AnalysisInstitutional AnalysisInstitutional EffectivenessComparative Institutional AnalysisComparative InstitutionsFunnel ChartsFunnel PlotsInstitutional BenchmarkingInstitutional Performance MeasurementShewhart Control Charts
Funnel plots are recommended as a graphical aid for institutional comparisons, plotting an estimate of an underlying quantity against a measure of its precision, with control limits forming a funnel around the target outcome analogous to Shewhart control charts. The authors illustrate how funnel plots can compare proportions and rate changes, assess the relationship between outcomes and case volume, and account for over‑dispersion from unmeasured risk factors. They conclude that funnel plots are flexible, attractively simple, and prevent spurious ranking of institutions into league tables. © 2004 John Wiley & Sons, Ltd.
Abstract ‘Funnel plots’ are recommended as a graphical aid for institutional comparisons, in which an estimate of an underlying quantity is plotted against an interpretable measure of its precision. ‘Control limits’ form a funnel around the target outcome, in a close analogy to standard Shewhart control charts. Examples are given for comparing proportions and changes in rates, assessing association between outcome and volume of cases, and dealing with over‐dispersion due to unmeasured risk factors. We conclude that funnel plots are flexible, attractively simple, and avoid spurious ranking of institutions into ‘league tables’. Copyright © 2004 John Wiley & Sons, Ltd.
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Bias in meta-analysis detected by a simple, graphical test
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Meta-analysis in clinical trials
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