Heterogeneity is commonplace in meta-analysis. When heterogeneity is found, researchers often aim to identify predictors that account for at least part of such heterogeneity by using mixed-effects meta-regression models. Another potentially relevant goal is to focus on the amount of heterogeneity as a function of one or more predictors, but this…

When meta-analyzing heterogeneous bodies of literature, meta-regression can be used to account for potentially relevant between-studies differences. A key challenge is that the number of candidate moderators is often high relative to the number of studies. This introduces risks of overfitting, spurious results, and model non-convergence. To…

Studies combined in a meta-analysis often have differences in their design and conduct that can lead to heterogeneous results. A random-effects model accounts for these differences in the underlying study effects, which includes a heterogeneity variance parameter. The DerSimonian-Laird method is often used to estimate the heterogeneity variance,…

Meta-analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between-study variability, which is typically modelled using a between-study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between-study variance,…

Heterogeneity in meta-analysis is most commonly estimated using a moment-based approach described by DerSimonian and Laird. However, this method has been shown to produce biased estimates. Alternative methods to estimate heterogeneity include the restricted maximum likelihood approach and those proposed by Paule and Mandel, Sidik and Jonkman, and…

The testing effect is a robust empirical finding in the research on learning and instruction, demonstrating that taking tests during the learning phase facilitates later retrieval from long-term memory. Early evidence came mainly from laboratory studies, though in recent years applied educational researchers have become increasingly interested in…

When classifying the evidence base of practices, special education scholars typically appraise study quality to identify and exclude from consideration in their reviews unacceptable-quality studies that are likely biased and might bias review findings if included. However, study quality appraisals used in the process of identifying evidence-based…

A meta-analyses was undertaken to determine the factors that are most related with reducing the achievement gap. The meta-analysis included 30 studies that examined attempts to bridge the achievement gap between White students on one hand and Black and Latino students on the other. The results indicate that several factors are associated with a…