Homogeneity analysis of test score data: A confrontation with the latent trait approach

Abstract

In homogeneity analysis, or dual scaling, weights for item categories are obtained that maximize Cronbach’s alpha. In this paper these weights are compared with the optimal scoring weights in the latent trait approach. This is done on the basis of data generated according to the two-parameter logistic model. As expected from a theoretical analysis, the homogeneity weights show less variation than the optimal weights of latent trait theory. It is argued that the homogeneity weights should not be used for item selection.