Visual Representations of Meta-Analyses of Multiple Outcomes: Extensions to Forest Plots, Funnel Plots, and Caterpillar Plots

Abstract

Meta-analytic datasets can be large, especially when in primary studies multiple effect sizes are reported. The visualization of meta-analytic data is therefore useful to summarize data and understand information reported in primary studies. The gold standard figures in meta-analysis are forest and funnel plots. However, none of these plots can yet account for the existence of multiple effect sizes within primary studies. This manuscript describes extensions to the funnel plot, forest plot and caterpillar plot to adapt them to three-level meta-analyses. For forest plots, we propose to plot the study-specific effects and their precision, and to add additional confidence intervals that reflect the sampling variance of individual effect sizes. For caterpillar plots and funnel plots, we recommend to plot individual effect sizes and averaged study-effect sizes in two separate graphs. For the funnel plot, plotting separate graphs might improve the detection of both publication bias and/or selective outcome reporting bias.