Robust Multivariate Analysis for the Comparison of Several Samples

We consider the problem of comparing samples drawn from several subpopulations when the data are multivariate. The method proposed is based on examining distances of all observations from the estimated locations of each sample. The distances examined are extensions of the Mahalanobis distance, where the classical means and covariances are replaced by robust estimates. The analysis of the distances is done by informal graphical methods. The method is illustrated by an example in which three groups of patients are compared with respect to thirteen variables measuring nerve conduction.