In this paper, individual differences scaling (INDSCAL) is revisited, considering
INDSCAL as being embedded within a hierarchy of individual difference scaling
models. We explore the members of this family, distinguishing (i) models, (ii) the
role of identification and substantive constraints, (iii) criteria for fitting models and (iv) algorithms to optimise the criteria. Model formulations may be based either on data that are in the form of proximities or on configurational matrices. In its configurational version, individual difference scaling may be formulated as a form of generalized Procrustes analysis. Algorithms are introduced for fitting the new
models. An application from sensory evaluation illustrates the performance of the
methods and their solutions
