INDIVIDUAL DIFFERENCES IN MULTIDIMENSIONAL SCALING*

Abstract

Applications of Tucker and Messick's model of individual differences in multidimensional scaling have suggested the occasional appropriateness of a refinement of that model. The refinement is to consider just one multidimensional stimulus space for all persons (or sets of persons) and with each person having a “weight” for each axis. This paper presents a formal description of this model and a least squares solution for its parameters. The solution has yet to be tested empirically.