This paper's objective was to teach the Equivalence Testing applied to Educational Research to emphasize recommendations and to increase quality of research. Equivalence Testing is a technique used to compare effect sizes or means of two different studies to ascertain if they would be statistically equivalent. For making accessible Equivalence…

The manuscript presents a Visual Basic[superscript R] for Applications function that operates within Microsoft Office Excel[superscript R] to return the area below the curve for a given F within a specified non-central F distribution. The function will be of use to Excel users without programming experience wherever a non-central F distribution is…

Odgaard and Fowler (2010) articulated the importance of reporting confidence intervals (CIs) on effect size estimates, and they provided useful formulas for doing so. However, one of their reported formulas, pertaining to the calculation of CIs on strength of association effect sizes (e.g., R[squared] or [eta][squared]), is erroneous. This comment…

Analysis of variance is one of the most frequently used statistical analyses in the behavioral, educational, and social sciences, and special attention has been paid to the selection and use of an appropriate effect size measure of association in analysis of variance. This article presents the sample size procedures for precise interval estimation…

Research has shown that forest plots are a gold standard in the visualization of meta-analytic results. However, research on the general interpretation of forest plots and the role of researchers' meta-analysis experience and field of study is still unavailable. Additionally, the traditional display of effect sizes, confidence intervals, and…

Two-phase designs in epidemiological studies of autism prevalence introduce methodological complications that can severely limit the precision of resulting estimates. If the assumptions used to derive the prevalence estimate are invalid or if the uncertainty surrounding these assumptions is not properly accounted for in the statistical inference…

The purpose of this meta-analysis was to determine the relation between mathematics and working memory (WM) and to identify possible moderators of this relation including domains of WM, types of mathematics skills, and sample type. A meta-analysis of 110 studies with 829 effect sizes found a significant medium correlation of mathematics and WM, r…

The call for researchers to report and interpret effect sizes and their corresponding confidence intervals has never been stronger. However, there is confusion in the literature on the definition of effect size, and consequently the term is used inconsistently. We propose a definition for effect size, discuss 3 facets of effect size (dimension,…

Researchers are strongly encouraged to accompany the results of statistical tests with appropriate estimates of effect size. For 2-group comparisons, a probability-based effect size estimator ("A") has many appealing properties (e.g., it is easy to understand, robust to violations of parametric assumptions, insensitive to outliers). We review…

In this study, the authors aimed to examine 8 of the different methods for computing confidence intervals around alpha that have been proposed to determine which of these, if any, is the most accurate and precise. Monte Carlo methods were used to simulate samples under known and controlled population conditions wherein the underlying item…

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…

Confidence intervals (CIs) and effect sizes are essential to encourage meta-analytic thinking and to accumulate research findings. CIs provide a range of plausible values for population parameters with a degree of confidence that the parameter is in that particular interval. CIs also give information about how precise the estimates are. Comparison…

Longitudinal studies are necessary to examine individual change over time, with group status often being an important variable in explaining some individual differences in change. Although sample size planning for longitudinal studies has focused on statistical power, recent calls for effect sizes and their corresponding confidence intervals…

When two or more univariate population means are compared, the proportion of variation in the dependent variable accounted for by population group membership is eta-squared. This effect size can be generalized by using multivariate measures of association, based on the multivariate analysis of variance (MANOVA) statistics, to establish whether…

One of the main objectives in meta-analysis is to estimate the overall effect size by calculating a confidence interval (CI). The usual procedure consists of assuming a standard normal distribution and a sampling variance defined as the inverse of the sum of the estimated weights of the effect sizes. But this procedure does not take into account…