Akaike's information criterion is suggested as a tool for evaluating fit and dimensionality in metric multidimensional scaling that uses least squares methods of estimation. This criterion combines the least squares loss function with the number of estimated parameters. Numerical examples are presented. The results from analyses of both simulation…

This paper describes the Confirmatory Factor Analysis (CFA) parameterization of the Profile Analysis via Multidimensional Scaling (PAMS) model to demonstrate validation of profile pattern hypotheses derived from multidimensional scaling (MDS). Profile Analysis via Multidimensional Scaling (PAMS) is an exploratory method for identifying major…

A model for test scores called the profile analysis via multidimensional scaling (PAMS) model is described. The model reparameterizes the linear latent variable model in such a way that the latent variables can be interpreted in terms of profile patterns, rather than factors. The model can serve as the basis for exploratory multidimensional…

Cross-validation procedures are proposed as a supplement to significance testing for external analysis of models relating stimulus preferences to known multidimensional scale values (Preference models). Examples of the usefulness of the validation procedures are provided. (Author/JKS)

Two of the most popular methods of profile analysis, cluster analysis and modal profile analysis, have limitations. First, neither technique is adequate when the sample size is large. Second, neither method will necessarily provide profile information in terms of both level and pattern. A new method of profile analysis, called Profile Analysis via…

Results of profile analysis via multidimensional scaling (PAMS), a technique for studying the most prominent profiles in a battery of measures, are reported for the Wechsler Adult Intelligence Scale--Revised (WAIS) and the General Aptitude Test Battery (GATB). PAMS profiles and the methodological features of the PAMS approach are discussed. (SLD)

Multidimensional scaling and factor analysis were applied to Rest's objective test of Kohlbergian moral development. The responses of 160 junior high, senior high, college undergraduate, and graduate students were analyzed in order to investigate whether stage and item scores displayed a hierarchial sequential structure. (Author/SS)

This study was designed to explain how Profile Analysis via Multidimensional Scaling (PAMS) could be viewed as a structural equations model (SEM). The study replicated the major profiles extracted from PAMS in the context of the latent variables in SEM. Data involved the Basic Theme Scales of the Strong Campbell Interest Inventory (Campbell and…

A reparameterization of the general Euclidean model for the external analysis of preference data and a simple least squares method for fitting the model to metric single stimulus data are discussed. The reformulated model is less general than is the earlier formulation by J. D. Carroll (1972). (SLD)

Describes use of multidimensional scaling (MDS) in counseling. Discusses types of data that have been analyzed using MDS, kinds of MDS analyses, and the interpretation of MDS results. Reviews MDS research relevant to vocational, family, group, and individual counseling. Also discusses potential applications in counseling practice. (Author/ABB)

This study described an explicit multidimensional scaling (MDS) model for profile data, the Profile Analysis via Multidimensional Scaling (PAMS) model. It also illustrated the application of this model to the study of the structure of cognitive ability patterns using the Woodcock-Johnson Psychoeducational Battery-Revised (WJPB-R; 1989; 1991) and…

This paper describes a methodology, called Profile Analysis via Multidimensional Scaling (PAMS), designed to identify major patterns of variables and to study the relationships into which those patterns enter. Patterns of variables are here called profiles. The PAMS procedure has been adapted to characteristics of the National Assessment of…

Assuming that subject responses rank order stimuli by preference, statistical methods are presented for testing the hypothesis that responses conform to a unidimensional, qualitative unfolding model and to an a priori stimulus ordering. The model is suitable for the analysis of structure in attitude responses, preference data, and developmental…

Latent growth curve modeling provides a powerful and flexible tool for researchers to study individual differences in change as well as the correlates and predictors of change. Recent developments in estimation and hypothesis testing procedures are largely based on confirmatory structural equation approaches. In this article, an alternative…

Academic psychology has long been composed of two disciplines, one experimental and one correlational. These two disciplines each developed their own method of studying structure in data: multidimensional scaling (MDS) and factor analysis. Both methods use similar kinds of input data, proximity measures on object pairs. Both represent the object…