Meta-analyses of educational research findings frequently involve statistically dependent effect size estimates. Meta-analysts have often addressed dependence issues using ad hoc approaches that involve modifying the data to conform to the assumptions of models for independent effect size estimates, such as by aggregating estimates to obtain one…

Researchers designing multisite and cluster randomized trials of educational interventions will usually conduct a power analysis in the planning stage of the study. To conduct the power analysis, researchers often use estimates of intracluster correlation coefficients and effect sizes derived from an analysis of survey data. When there is…

Meta-analysis is a statistical technique that allows an analyst to synthesize effect sizes from multiple primary studies. To estimate meta-analysis models, the open-source statistical environment R is quickly becoming a popular choice. The meta-analytic community has contributed to this growth by developing numerous packages specific to…

Meta-analyses often include studies that report multiple effect sizes based on a common pool of subjects or that report effect sizes from several samples that were treated with very similar research protocols. The inclusion of such studies introduces dependence among the effect size estimates. When the number of studies is large, robust variance…

A latent variable modeling method is outlined for constructing a confidence interval (CI) of a popular multivariate effect size measure. The procedure uses the conventional multivariate analysis of variance (MANOVA) setup and is applicable with large samples. The approach provides a population range of plausible values for the proportion of…

Provides an overall test statistic to evaluate significance that yields 100% (1-alpha) confidence intervals for all linear combinations of effect sizes, shows how the stepdown Finite Intersection Test (N. Timm, 1995) may be used to test whether effect sizes are simultaneously different from zero, and illustrates the procedure. (SLD)

Shows how to test the hypothesis that a nonnested model fits a set of predictors when modeling multiple effect sizes in meta-analysis. Illustrates the procedure using data from previous studies of the effectiveness of coaching on performance on the Scholastic Aptitude Test. (SLD)