Ft statistic test is a non classical method of comparing two or more groups. This statistical procedure is able to handle problems of sample locations when non-normality occurs but the homogeneity of variances assumption still applies. This method is not robust under the existence of variance heterogeneity. To make this test less sensitive when either one or both of the common assumptions are violated, in this study the test is modified and improved by replacing the test’s original central tendency measure that is, the fixed symmetric trimmed mean with a predetermined asymmetric trimmed mean and a modified one-step M-estimator (MOM) trimmed mean. The finding shows that when the data is suspected to be extremely skewed, then, it will be advantageous to adopt MOM procedures for homogeneous variance cases. On the other hand, for heterogeneous variances, a trimmed mean which uses predetermined asymmetric trimmed mean should be considered as an alternative, particularly for testing the equality of four groups.
Key words: Heterogeneity, asymmetric, trimmed mean, MOM, robustness.
Copyright © 2022 Author(s) retain the copyright of this article.
This article is published under the terms of the Creative Commons Attribution License 4.0