Abstract
A quantification method was developed for sorting data collected over a sample of subjects. Given multiple sets of sorting data this method finds, in a multidimensional Euclidian space, a configuration of points in such a way that the sum of squared inter-cluster distances averaged over subjects is maximized under suitable normalization conditions. Examples were given to illustrate the use of the method and its relationship to other scaling methods was discussed.
