Using the normal quantile plot to explore meta-analytic data sets.

In a meta-analysis, graphical displays can be used to check statistical assumptions for numerical procedures and they can be used to discover important patterns in the data. The authors propose the normal quantile plot as a preferred alternative to the funnel plot for such purposes. The normal quantile plot, like the funnel plot, can be used to investigate whether all studies come from a single population and to search for publication bias. However, the normal quantile plot is easier to interpret than the funnel plot, especially when it includes 95% confidence bands. In addition, the normal quantile plot can be used to check the normality assumption for numerical procedures. The funnel plot cannot be used for this latter purpose. Most people have heard the phrase, A picture is worth a thousand words. This phrase seems especially applicable to producers and consumers of metaanalytic reviews. In a meta-analysis, graphical displays (figures, plots) can be used to enhance numerical analyses in at least two ways. First, graphical displays can be used to discover patterns and relations among variables in a meta-analysis. Second, graphical displays can be used to check statistical assumptions on which numerical analyses are based. One of the most popular graphical displays for exploring meta-analytic data sets is the funnel plot (Light & Pillemer, 1984). In this article, we begin by describing the funnel plot and its uses. We then propose the normal quantile plot as a preferred alternative to the funnel plot.