The kinds of individual differences in perceptions permitted by the weighted euclidean model for multidimensional scaling are more restrictive than those allowed by models developed by Tucker or Carroll. It is shown how problems which occur when using the more general models can be removed. (Author/JKS)

Author argues that simplistic and/or heuristic approaches to the Tucker and Messick model (an individual differences model for multidimensional scaling, 1963) are often inadequate. (Author/CB)

The degree to which Procrustean Individual Differences Scaling can be extended to related topics such as target analysis is discussed and a Monte Carlo study investigating the fit of the model under various conditions is presented. (JKS)

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)

Concerned with another form of analysis of m sets of matrices, the Procrustes idea is generalized so that all m sets are simultaneously translated, rotated, reflected and scaled so that a goodness of fit criterion is optimised. A computational technique is given, results of which can be summarized in analysis of variance form. (RC)