The present article provides a primer on using effect sizes in research. A small heuristic data set is used in order to make the discussion concrete. Additionally, various admonitions for best practice in reporting and interpreting effect sizes are presented. Among these is the admonition to not use Cohen's benchmarks for "small," "medium," and…

This article sets the context for the development of research quality indicators and guidelines for evidence of effective practices provided by different methodologies. The current conceptualization of scientific research in education and the complexity of conducting research in special education settings underlie the development of quality…

The present article presents a tutorial on how to estimate and interpret various effect sizes. The 5th edition of the Publication Manual of the American Psychological Association (2001) described the failure to report effect sizes as a "defect" (p. 5), and 23 journals have published author guidelines requiring effect size reporting. Although…

This paper provides an introduction to basic issues concerning structural equation modeling (SEM), a research methodology increasingly being used in social science research. First, seven key issues that must be considered in any SEM analysis are explained. These include matrix of associations to analyze, model identification, parameter estimation…

Surveyed AERA members regarding their perceptions of: statistical issues and statistical significance testing; the general linear model; stepwise methods; score reliability; type I and II errors; sample size; statistical probabilities as exclusive measures of effect size; p values as direct measures of result value; and p values evaluating…

Given decades of lucid, blunt admonitions that statistical significance tests are often misused, and that the tests are somewhat limited in utility, what is needed is less repeated bashing of statistical tests, and some honest reflection regarding the etiology of researchers' denial and psychological resistance (sometimes unconscious) to improved…

As an extension of B. Thompson's 1998 invited address to the American Educational Research Association, this paper cites two additional common faux pas in research methodology and explores some research issues for the future. These two errors in methodology are the use of univariate analyses in the presence of multiple outcome variables (with the…

In early intervention, researchers often are interested in interpretation aids that can help determine the relative importance of variables when multiple regression models are used, and that facilitate deeper insight into prediction dynamics. Commonality analysis is one approach for helping researchers understand the contributions independent or…