Abstract
It is well known that the conventional method for comparing j independent groups, one-way ANOVA F-test, depends on normal theory assumptions. In this study, a new test is proposed which is based on a one-step M-estimator and a bootstrap-t method. ANOVA F-Test, a test which compares J population’s M-measures of location by using Schrader and Hettmansperger test statistic, a test which also compares M-measures of location by using Liu-Singh’s limiting p-values notion with a percentile bootstrap approach and the proposed test were compared in terms of saving nominal Type I error via Monte Carlo simulations. It was found that the proposed test compares well under normality and homogeneity and it was much more preferable than those three tests under non-normality and heterogeneity of variances.
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