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

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.

Estimation of the biserial correlation and its sampling variance for use in meta‐analysis

“…Forest plots are frequently used in meta-analyses to present the findings of the individual studies (Schild and Voracek, 2013). For each study, the plot shows the observed value of the outcome measure of interest (e.g., correlation coefficient) and the corresponding confidence interval (usually 95%) for the study's true outcome (Lewis and Clarke, 2001).…”

Cross‐hairs: a scatterplot for meta‐analysis in R

“…Graphs are an excellent way to represent data in a meta‐analysis (Anzures‐Cabrera and Higgins, ; Borenstein et al ., ). Despite the value of graphs for providing insight, several kinds of graphs are rarely used, and graphs are more likely to be used in medical journals than in social science journals, at least for psychology and business (Schild and Voracek, ). In their primer, Anzures‐Cabrera and Higgins () noted four main types of graphs used in meta‐analysis: forest plots, funnel plots, Galbraith plots, and L'Abbé plots.…”

“…In their primer, Anzures‐Cabrera and Higgins () noted four main types of graphs used in meta‐analysis: forest plots, funnel plots, Galbraith plots, and L'Abbé plots. Forest plots appear to be the most commonly published (Schild and Voracek, ).…”

Finding your way out of the forest without a trail of bread crumbs: development and evaluation of two novel displays of forest plots

“…This common design of forest plots has repeatedly been criticized (Barrowman and Myers, 2003;Jackson, 2008;Anzures-Cabrera and Higgins, 2010;Schriger et al, 2010;Schild and Voracek, 2013), and three points have been put forward: First, small studies may attract an undue amount of attention because of their long confidence intervals. Although small studies have less impact on the overall pooled result, they may appear more visually striking than larger ones.…”