In this interview, we discuss my early uses of meta-analytic procedures, first to combine "p"-values and then to combine effect sizes as well. My interest in quantifying the magnitude and the statistical significance of the effect of interpersonal expectations probably grew out of the following: (1) a long-held interest in the concept of…

The binomial effect size display (BESD) displays the change in success rate attributable to a treatment procedure. It is readily understandable, applicable in varied contexts, and conveniently computed. (Author/GK)

Presents the strategic advantages of focused over omnibus tests of statistical significance in counseling research, and demonstrates the utility of interpreting the magnitude of the effect as a way of assessing practical significance (i.e., in addition to computing "p" levels). Gives simple procedures for computing effect size using the…

This article presents a system for avoiding Type I error increases when increasing the number of contrasts computed. Based on the Bonferroni inequality, the procedure corrects for the number of contrasts tested. Although conservative, the Bonferroni system is recommended for its flexibility, simplicity, and generality. (Author/BS)

An overview of the state of the art in psychological research is presented, with an emphasis on the attention given to effect sizes. The acceptance of small effect sizes for biomedical research is contrasted with the rejection of similar effect sizes for psychological research. The Binomial Effect Size Display is used to depict the practical…

Shares three ideas concerning how to evaluate the practical importance of developmental findings to make them more useful to policymakers: (1) statistical significance tests need to be accompanied by effect size estimates; (2) meta-analyses are helping in using all existing data when examining issues involved in policy debates; and (3) researchers…