ALEXANDER AND GOVERNS APPROXIMATION - PROVIDING AN ALTERNATIVE TO ANOVA UNDER VARIANCE HETEROGENEITY

A Monte Carlo simulation was conducted to compare the Type I error rat e and power of the 1994 approximation developed by Alexander and Gover n as an alternative to the ANOVA F test. It was compared with the ANOV A F, Kruskal-Wallis, Welch, Brown-Forsythe, and James second-order tes ts. The authors concentrated on the impact of various factors on Type I error rate and power. The factors included variance inequality, samp le-size pairings with group variances, degree of skewness/kurtosis, an d number of treatment groups. Under variance heterogeneity, Alexander- Govern's test was not only comparable to the performance of the Welch test and the James second-order test but was superior in certain insta nces.