A gradient method is used to obtain least squares estimates of parameters in constrained multidimensional scaling in N spaces. Features and constraints of the method and two applications of the procedure are presented. (Author/JKS)

A family of models for the representation and assessment of individual differences for multivariate data called PINDIS (Procrustean Individual Differences Scaling) is presented. PINDIS sheds new light on the interpretability and applicability of a variety of multidimensional scaling models. (Author/JKS)

Two lines of psychometric interest are combined: a) multidimensional scaling and, b) factor analysis. This is achieved by employing three-mode factor analysis of scalar product matrices, one for each subject. Two of the modes are the group of objects scaled and the third is the sample of subjects. Resulting from this are, an object space, a person…

Many data analysis problems in psychology may be posed conveniently in terms which place the parameters to be estimated on one side of an equation and an expression in these parameters on the other side. A rule for improving the rate of convergence of the iterative solution of such equations is developed and applied to four problems. (Author/RC)