The authors examined the distributional properties of 3 improvement-over-chance, I, effect sizes each derived from linear and quadratic predictive discriminant analysis and from logistic regression analysis for the 2-group univariate classification. These 3 classification methods (3 levels) were studied under varying levels of data conditions, including population separation (3 levels), variance pattern (3 levels), total sample size (3 levels), and prior probabilities (5 levels). The results indicated that the decision of which effect size to choose is primarily determined by the variance pattern and prior probabilities. Some of the "I" indices performed well for some small sample cases and quadratic predictive discriminant analysis "I" tended to work well with extreme variance heterogeneity and differing prior probabilities.