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

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 g...

Full description

Saved in:
Bibliographic Details
Published in:Research synthesis methods 2013-09, Vol.4 (3), p.209-219
Main Authors: Schild, Anne H. E., Voracek, Martin
Format: Article
Language:English
Subjects:
Algorithms
Business
Comparative Analysis
Computer Graphics
Computer Software
Correlation
Data Interpretation, Statistical
Data Mining - methods
Differences
forest plot
graph
Graphs
Interdisciplinary Approach
Medicine
Meta Analysis
Meta-Analysis as Topic
Natural Language Processing
Psychology
Research methodology
research synthesis
Resistance (Psychology)
Systematic review
User-Computer Interface
Visualization
Vocabulary, Controlled
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:1759-2879
1759-2887
DOI:10.1002/jrsm.1076