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 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 HighWire Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Wilcox, R. R. Search for Related Content Social Bookmarking                         What's this?

ANOVA: A Paradigm for Low Power and Misleading Measures of Effect Size?

University of Southern California

Over 30 years ago, Tukey made it evident that slight departures from normality can substantially lower power when means are compared, and that a popular measure of effect size can be highly misleading. At the time there were no methods for dealing with the problem raised in Tukey’s paper, and some of the more obvious and seemingly intuitive solutions have since been found to be highly unsatisfactory. Today there are practical methods for not only dealing with the problem raised by Tukey, but also achieving more accurate confidence intervals and control over the probability of a Type I error. More generally, there are many robust and exploratory ways of comparing groups that can reveal important differences that are missed by conventional methods based on means, and even modern methods based solely on robust measures of location. This article reviews these new techniques.

Review of Educational Research, Vol. 65, No. 1, 51-77 (1995)
DOI: 10.3102/00346543065001051


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

This article has been cited by other articles:

				L. M. Lix and H. J. Keselman Multivariate Tests of Means in Independent Groups Designs: Effects of Covariance Heterogeneity and Nonnormality Eval Health Prof, March 1, 2004; 27(1): 45 - 69. [Abstract] [PDF]

				H. J. Keselman, C. J. Huberty, L. M. Lix, S. Olejnik, R. A. Cribbie, B. Donahue, R. K. Kowalchuk, L. L. Lowman, M. D. Petoskey, J. C. Keselman, et al. Statistical Practices of Educational Researchers: An Analysis of their ANOVA, MANOVA, and ANCOVA Analyses Review of Educational Research, January 1, 1998; 68(3): 350 - 386. [Abstract] [PDF]

				W. T. Coombs, J. Algina, and D. O. Oltman Univariate and Multivariate Omnibus Hypothesis Tests Selected to Control Type I Error Rates When Population Variances Are Not Necessarily Equal Review of Educational Research, January 1, 1996; 66(2): 137 - 179. [Abstract] [PDF]

				L. M. Lix, J. C. Keselman, and H. J. Keselman Consequences of Assumption Violations Revisited: A Quantitative Review of Alternatives to the One-Way Analysis of Variance F Test Review of Educational Research, January 1, 1996; 66(4): 579 - 619. [Abstract] [PDF]