Two potentially useful tests for homogeneity of variance--the jackknife test and the Box test--are described and compared. Recommendations for the use of these techniques and computational examples of each are provided. (Author/JKS)

This paper describes how to determine whether enough observations have been sampled to be reasonably certain that a correct decision will be made about how the difference between the means of an experimental and control group compares to a constant specified by the experimenter. Equal variances are not assumed. (Author/BW)

Seven univariate procedures for testing omnibus null hypotheses for data gathered from repeated measures designs were evaluated, comparing five alternative approaches with two more traditional procedures. Results suggest that the alternatives are improvements. The most effective alternate procedure in controlling Type I error rates is discussed.…

The analysis of variance, Welch, and Brown and Forsyth tests for mean equality were compared using Monte Carlo methods. The tests' rates of Type I error and power were examined when populations were nonnormal, variances were heterogeneous, and group sizes were unequal. Recommendations for use are presented. (Author/JKS)

The alternative proposed by Wilcox (1989) to the James second-order statistic for comparing population means when variances are heterogeneous can sometimes be invalid. The degree to which the procedure is invalid depends on differences in sample size, the expected values of the observations, and population variances. (SLD)

Compares three methods of analyzing pairwise treatment differences in a multi-treatment experiment via computer simulation techniques. Under the equal n condition, the robustness of the conventional Tukey Wholly Significant Difference test (WSD) to heterogeneous variances was contrasted with two alternate techniques. Under unequal n conditions,…

This paper investigates three methods for comparing medians rather than means in studying two independent treatment groups. The method that gave the best results is based on a normal approximation of the distribution of the sample median where the variance is estimated using results reported by Maritz and Jarrett. (Author/JAZ)