This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in Web of Science Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Web of Science (1) Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Natesan, P. Articles by Thompson, B. Search for Related Content Social Bookmarking                         What's this?

Extending Improvement-Over-Chance I-Index Effect Size Simulation Studies to Cover Some Small-Sample Cases

Texas A&M University, College Station

Bruce Thompson

Texas A&M University, College Station; Baylor College of Medicine, Houston, Texas, bruce-thompson{at}tamu.edu

All effect sizes are sensitive to design flaws and the failure to meet analytic assumptions. But some effect sizes appear to be more robust to assumption violations (e.g., homogeneity of variance). The present study extended prior Monte Carlo research by exploring the robustness of group overlap I indices at the relatively small sample sizes used in some research. I effects are statistically appealing because these indices can be applied across (a) both univariate and multivariate analyses and (b) conditions of either variance homogeneity or variance heterogeneity.

Key Words: effect size • statistical significance • practical significance • clinical significance • simulation studies

Educational and Psychological Measurement, Vol. 67, No. 1, 59-72 (2007)
DOI: 10.1177/0013164406292028


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?