A Primer on Basic Effect Size Concepts.

N

13

Effect Size; Research Design; Statistical Significance

The increased interest in reporting effect sizes means that it is necessary to consider what should be included in a primer on effect sizes. A review of papers on effect sizes and commonly repeated statistical analyses suggests that it is important to discuss effect sizes relative to bivariate correlation, t-tests, analysis of variance/covariance, and multiple regression/correlation. An agreed upon nomenclature regarding effect sizes should be established. R. Rosenthal (1994) has classified effect sizes into the "r" family (the Pearson product moment correlation coefficient and the various squared indices of "r" and "r"-type quantities) and the "d" family (mean difference and standardized mean difference indices). Other measures of effect size have been suggested, and some suggestions are given for further reading on these measures. Parsimony and replication should be joined by meaning as principles to consider in reporting research results. To enhance meaning and interpretability of research findings, it is essential that various psychometric variables and test scores be studied and reported for specific samples under varied conditions. (Contains 29 references.) (SLD)

2001

ED453260