The effect of unequal priors and unequal misclassification costs on MDA

Abstract

Multiple discriminant analysis (MDA) is a frequently used statistical technique. Although the dependence of this technique on the underlying assumptions concerning population priors and misclassification costs is well known, the assumption most often made by researchers is that both population priors and misclassification costs are equal. The purpose of this paper is to demonstrate the magnitude of the effect of these assumptions on statistical results. In the savings and loan case used here, the population priors are known:however, the relative misclassification costs are not. To test the sensitivity of the results to the unknown misclassification costs several different misclassification cost assumptions are used.