The relationship between variance components and mean difference effect size

Variance components in the context of Generalizability Theory are useful in dices for attributing the amount of variance to a particular facet or objec t of measurement. The mean difference effect size (MDES) has proven to be a useful tool both in synthesizing the results of multiple studies and in in terpreting individual study results. A mathematical relationship is drawn, therefore, between the variance components of a nested two-facet design con figuration on the one hand, and the MDES that can be calculated from the de scriptive statistics of an hypothetical measurement study on the other. Usi ng two different variance components estimation procedures, we show that th e relationship is both statistically and conceptually meaningful in that al l of these estimates closely approximates the true Glassian MDES.