Estimates of Location Based on Rank Tests

Abstract

A serious objection to many of the classical statistical methods based on linear models or normality assumptions is their vulnerability to gross errors. For certain testing problems this difficulty is suc-cessfully overcome by rank tests such as the two Wilcoxon tests or the Kruskal- Wallis H-test. Their power is more robust against gross errors than that of the t- and F-tests, and their efficiency loss is quite small even in the rare case in which the suspicion of the possibility of gross errors is unfounded.