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Graphical displays for meta‐analysis: An overview with suggestions for practice
Author(s) -
AnzuresCabrera Judith,
Higgins Julian P. T.
Publication year - 2010
Publication title -
research synthesis methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.376
H-Index - 35
eISSN - 1759-2887
pISSN - 1759-2879
DOI - 10.1002/jrsm.6
Subject(s) - computer science , graphical model , statistical graphics , funnel plot , univariate , data science , bayesian probability , presentation (obstetrics) , meta analysis , information retrieval , data mining , plot (graphics) , principal (computer security) , publication bias , graphics , machine learning , artificial intelligence , statistics , computer graphics (images) , mathematics , multivariate statistics , medicine , radiology , operating system
Meta‐analyses are fundamental tools for collating and synthesizing large amounts of information, and graphical displays have become the principal tool for presenting the results of multiple studies of the same research question. We review standard and proposed graphical displays for presentation of meta‐analytic data, and offer our recommendations on how they might be presented to provide the most useful and user‐friendly illustrations. We concentrate on graphs that specifically aim to present similar sorts of univariate results from multiple studies. We start with forest plots and funnel plots, and proceed to Galbraith (or radial) plots, L'Abbé (and related) plots, further plots useful for investigating heterogeneity, plots useful for model diagnostics and plots for illustrating likelihoods and Bayesian meta‐analyses. Copyright © 2010 John Wiley & Sons, Ltd.