Standardized effects and precision boundaries
The Galbraith plot (also called radial plot) divides standardized effect size by its standard error, plotting it against precision (inverse standard error). Each study is a dot. The center origin represents zero effect; studies to the right show positive effects, those to the left show negative effects. Distance from the center reflects magnitude of standardization.
Horizontal dotted lines at +2 and -2 standard errors mark the conventional 95% boundary. Studies between these lines represent statistically consistent findings; studies outside them are outliers disagreeing significantly with the meta-analytic estimate. The plot efficiently flags heterogeneous studies in a single visualization.
Finding sources of study heterogeneity
A Galbraith plot crowded near the center with few outliers suggests homogeneous results. Plots scattered widely signal heterogeneity; outliers on one side or the other hint at subgroups or methodological differences driving disagreement. Investigating outlier studies often reveals design choices, patient populations, or intervention variations explaining divergence.
Unlike forest plots, which organize studies sequentially, Galbraith plots display all relationships simultaneously, making pattern spotting easier. A cluster of negative outliers versus a cluster of positive ones might suggest that study design, publication bias, or true variation by population drives the disagreement.