Literature DB >> 26053841

Less is less: a systematic review of graph use in meta-analyses.

Anne H E Schild1, Martin Voracek2.   

Abstract

Graphs are an essential part of scientific communication. Complex datasets, of which meta-analyses are textbook examples, benefit the most from visualization. Although a number of graph options for meta-analyses exist, the extent to which these are used was hitherto unclear. A systematic review on graph use in meta-analyses in three disciplines (medicine, psychology, and business) and nine journals was conducted. Interdisciplinary differences, which are mirrored in the respective journals, were revealed, that is, graph use correlates with external factors rather than methodological considerations. There was only limited variation in graph types (with forest plots as the most important representatives), and diagnostic plots were very rare. Although an increase in graph use over time could be observed, it is unlikely that this phenomenon is specific to meta-analyses. There is a gaping discrepancy between available graphic methods and their application in meta-analyses. This may be rooted in a number of factors, namely, (i) insufficient dissemination of new developments, (ii) unsatisfactory implementation in software packages, and (iii) minor attention on graphics in meta-analysis reporting guidelines. Using visualization methods to their full capacity is a further step in using meta-analysis to its full potential.
Copyright © 2013 John Wiley & Sons, Ltd.

Keywords:  forest plot; graph; meta-analysis; research synthesis; systematic review

Mesh:

Year:  2013        PMID: 26053841     DOI: 10.1002/jrsm.1076

Source DB:  PubMed          Journal:  Res Synth Methods        ISSN: 1759-2879            Impact factor:   5.273


  3 in total

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Authors:  Dustin A Fife; Gabrielle Longo; Michael Correll; Patrice D Tremoulet
Journal:  Behav Res Methods       Date:  2021-02-25

2.  Charting the landscape of graphical displays for meta-analysis and systematic reviews: a comprehensive review, taxonomy, and feature analysis.

Authors:  Michael Kossmeier; Ulrich S Tran; Martin Voracek
Journal:  BMC Med Res Methodol       Date:  2020-02-07       Impact factor: 4.615

3.  An evaluation of harvest plots to display results of meta-analyses in overviews of reviews: a cross-sectional study.

Authors:  Katelynn Crick; Aireen Wingert; Katrina Williams; Ricardo M Fernandes; Denise Thomson; Lisa Hartling
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  3 in total

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