A new procedure for nonmetric multidimensional scaling is proposed and evaluated in this extensive article. The procedure generalizes to a wide variety of situations and types of data and is robust with respect to measurement error. The statistical development of the procedure and examples of its use are presented. (JKS)

A maximum likelihood procedure is developed for multidimensional scaling where similarity or dissimilarity measures are taken by such ranking procedures as the method of conditional rank orders or the method of triadic combinations. An example is given. (Author/JKS)

A model is proposed in which different sets of linear constraints are imposed on different dimensions in component analysis and classical multidimensional scaling frameworks. An algorithm is presented for fitting the model to the data by least squares. Examples demonstrate the method. (SLD)

Ideal point discriminant analysis (IPDA) is proposed for the analysis of contingency tables of cross-classified data. Several data sets illustrate IPDA, which combines log-linear and dual scaling models to provide a spatial representation of row and column categories and allow statistical evaluation of various structural hypotheses about…

A maximum likelihood estimation procedure is developed for the simple and the weighted additive models. The data are assumed to be taken by either one of the following methods: (1) categorical ratings--the subject is asked to rate a set of stimuli with respect to an attribute of the stimuli on rating scales with a relatively few observation…

A maximum likelihood estimation procedure was developed to fit weighted and unweighted additive models of conjoint data obtained by categorical rating, paired comparisons or directional ranking methods. Practical uses of the procedure are presented to demonstrate various advantages of the procedure as a statistical method. (Author/JKS)

An individual differences additive model is discussed which represents individual differences in additivity by differential weighting or additive factors. A procedure for estimating model parameters for various data measurement characteristics is developed. The method is found to be very useful in describing certain types of developmental change…

A new method of multiple discriminant analysis allows a mixture of continuous and discrete predictors. It handles conditional, joint, or separate sampling. Subjects and criterion groups are represented as points in a multidimensional Euclidean space. Advantages of the method, deriving from Akaike Information Criterion model evaluation, are…