Graphical methods for detecting bias in meta-analysis

Abstract

The trustworthiness of meta-analysis, a set of techniques used to quantitatively combine results from different studies, has recently been questioned. Problems with meta-analysis stem from bias in selecting studies to include in a meta-analysis and from combining study results when it is inappropriate to do so. Simple graphical techniques address these problems but are infrequently applied. Funnel plots display the relationship of effect size versus sample size and help determine whether there is likely to have been selection bias in including studies in the meta-analysis. The L'Abbe plot displays the outcomes in both the treatment and control groups of included studies and helps to decide whether the studies are too heterogeneous to appropriately combine into a single measure of effect.