Comparing the variances of two dependent variables

Abstract

Various methods have been derived that are designed to test the hypothesis that two dependent variables have a common variance. Extant results indicate that all of these methods perform poorly in simulations. The paper provides a new perspective on why the Morgan-Pitman test does not control the probability of a Type I error when the marginal distributions have heavy tails. This new perspective suggests an alternative method for testing the hypothesis of equal variances and simulations indicate that it continues to perform well in situations where the Morgan-Pitman test performs poorly.