This paper includes a nontechnical description of methods for calculating effect sizes in intellectual and developmental disability studies. Different hypothetical studies are used to illustrate how null hypothesis significance testing (NHST) and effect size findings can result in quite different outcomes and therefore conflicting results. Whereas…

Over the years, methodologists have been recommending that researchers use magnitude of effect estimates in result interpretation to highlight the distinction between statistical and practical significance (cf. R. Kirk, 1996). A magnitude of effect statistic (i.e., effect size) tells to what degree the dependent variable can be controlled,…

The random variable p and its functions figure in several "tests of combined significance," meta-analysis summaries based on sample significance values, and ps have been used singly, as well as in other tests for evaluating the outcomes of individual research studies. In this work, asymptotic distributions of the sample one-sided…

Power is an indicator of the ability of a statistical analysis to detect a phenomenon that does in fact exist. The issue of power is crucial for social science research because sample size, effects, and relationships studied tend to be small and the power of a study relates directly to the size of the effect of interest and the sample size.…

Measures of effect size were computed for 237 statistical tests from 59 early intervention studies. Data revealed that the average treatment effect across studies was medium in size. Interpretation of measures of magnitude strength is discussed in relation to statistical significance testing. Reporting of measures of effect size along with…

This paper reviews criticism on misinterpretation and overuse of significance testing in the social sciences and examines use of effect size measures to enhance interpretation of significance testing. Review of typical effect size measures and their application is followed by analysis of use of effect size measures in studies reported over 10…

This tutorial summarizes some of the widely known limitations of tests of statistical significance and then focuses on extracting measures of variation accounted for as a supplement to significance testing. Two measures of variation accounted for, eta squared and omega squared, are discussed. Computational formulas, computational examples, and…

The purpose of this paper is to demonstrate how multiple linear regression provides a viable statistical methodology for dealing with meta-analysis in general, and specifically with the issues of nonindependence and design complexity, such as multiple treatments. Since the F-test and t-test are special cases of the general linear model,…

A general model is described which can be used to represent the four common types of meta-analysis: (1) estimation of effect size by combining study outcomes; (2) estimation of effect size by contrasting study outcomes; (3) estimation of statistical significance by combining study outcomes; and (4) estimation of statistical significance by…

The present essay outlines how mixed methods research can be used to enhance the interpretation of significant findings. First, we define what we mean by significance in educational evaluation research. With regard to quantitative-based research, we define the four types of significance: statistical significance, practical significance, clinical…

Surveyed older adolescents (N=2,313) to examine the effects of family size, birth order, and sibling spacing and gender upon perceptions of parent-adolescent relationships. Using the analysis of techniques of past studies, significant associations were found for family size, birth order, and spacing, although the effect sizes were quite small.…

This paper discusses distribution theory and power computations for four common "tests of combined significance." These tests are calculated using one-sided sample probabilities or p values from independent studies (or hypothesis tests), and provide an overall significance level for the series of results. Noncentral asymptotic sampling…

This paper evaluates the logic underlying various criticisms of statistical significance testing and makes specific recommendations for scientific and editorial practice that might better increase the knowledge base. Reliance on the traditional hypothesis testing model has led to a major bias against nonsignificant results and to misinterpretation…

Data drawn from 30 journal articles and ERIC documents reporting on gender differences in natural science achievement were re-examined. Three meta-analysis methods were used: (1) vote counts and vote-counting estimation procedures; (2) tests of combined significance; and (3) analyses of effect sizes. The three methods produced seemingly…