This article presents methods for using extant data to improve the properties of estimators of the standardized mean difference (SMD) effect size. Because samples recruited into education research studies are often more homogeneous than the populations of policy interest, the variation in educational outcomes can be smaller in these samples than…

Multiple baseline (MB) designs are becoming more prevalent in educational and behavioral research, and as they do, there is growing interest in combining effect size estimates across studies. To further refine the meta-analytic methods of estimating the effect, this study developed and compared eight alternative methods of estimating intervention…

In studies where the response variable is measured on a ratio scale, a ratio of means or medians provides a standardized measure of effect size that is an alternative to the popular standardized mean difference. Confidence intervals for ratios of population means and medians in independent-samples designs and paired-samples designs are proposed as…

The analysis of variance (ANOVA) is one of the most frequently used statistical analyses in practical applications. Accordingly, the single and multiple comparison procedures are frequently applied to assess the differences among mean effects. However, the underlying assumption of homogeneous variances may not always be tenable. This study…

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…

Multilevel modeling techniques are becoming more popular in handling data with multilevel structure in educational and behavioral research. Recently, researchers have paid more attention to cross-classified data structure that naturally arises in educational settings. However, unlike traditional single-level research, methodological studies about…

In single-case research, the multiple baseline design is a widely used approach for evaluating the effects of interventions on individuals. Multiple baseline designs involve repeated measurement of outcomes over time and the controlled introduction of a treatment at different times for different individuals. This article outlines a general…

This paper examines the impact of quality-score weights in meta-analysis. A simulation examines the roles of study characteristics such as population effect size (ES) and its variance on the bias and mean square errors (MSEs) of the estimators for several patterns of relationship between quality and ES, and for specific patterns of systematic…

Research designs involving cluster randomization are becoming increasingly important in educational and behavioral research. Many of these designs involve two levels of clustering or nesting (students within classes and classes within schools). Researchers would like to compute effect size indexes based on the standardized mean difference to…

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…

Experimental designs that randomly assign entire clusters of individuals (e.g., schools and classrooms) to treatments are frequently advocated as a way of guarding against contamination of the estimated average causal effect of treatment. However, in the absence of contamination, experimental designs that randomly assign intact clusters to…

In randomized control trials (RCTs) in the education field, the complier average causal effect (CACE) parameter is often of policy interest, because it pertains to intervention effects for students who receive a meaningful dose of treatment services. This article uses a causal inference and instrumental variables framework to examine the…

In this article, the authors outline methods for using fixed and random effects power analysis in the context of meta-analysis. Like statistical power analysis for primary studies, power analysis for meta-analysis can be done either prospectively or retrospectively and requires assumptions about parameters that are unknown. The authors provide…

A new effect size representing the predictive power of an independent variable from a multiple regression model is presented. The index, denoted as r[subscript sp], is the semipartial correlation of the predictor with the outcome of interest. This effect size can be computed when multiple predictor variables are included in the regression model…

There is widespread interest in using various statistical inference tools as a part of the evaluations for individual teachers and schools. Evaluation systems typically involve classifying hundreds or even thousands of teachers or schools according to their estimated performance. Many current evaluations are largely based on individual estimates…