Monte Carlo procedures are used to develop stress distributions using Kruskal's second stress formula. These distributions can be used in multidimensional scaling procedures to determine whether a set of data has other than random structure. (Author/JKS)

Techniques are developed for constructing confidence regions for each of the points in a multidimensional scaling solution. Bayesian credibility regions are discussed, and a technique for displaying these regions is described. (Author/JKS)

Two popular models for performing multidimensional scaling, Tucker and Messick's points-of-view model, and Tucker's three mode model, are combined into a single analytic procedure, the 3M-POV model. The procedure is described and its strengths are discussed. Carroll and Chang's INDSCAL model is also mentioned. (JKS)

A procedure is described for minimizing perspective error when calculating a scaling factor for any subject at any perpendicular distance from a camera, provided the subject touches the ground, and represents one way in which perspective error can be used to provide valuable information. (MJB)

Exploratory multidimensional scaling and confirmatory nonparametric procedures were used to represent data from similarity rating and sorting tasks on nine animal names administered prior to and following the reading of two stories using those names as main characters. Changes in structure were related to authors' intent. (Author/JKS)

Two-dimensional euclidean planes and additive trees are two of the most common representations of proximity data for multidimensional scaling. Guidelines for comparing these representations and discovering properties that could help identify which representation is more appropriate for a given data set are presented. (Author/JKS)

A general method of scaling pairwise preference data is presented that may be used without prior knowledge about the nature of the relationship between an observation and the process giving rise to it. The method involves a monotone transformation and is similar to the B-SPLINE approach. (Author/JKS)

A computational method for weighted euclidean distance scaling (a method of multidimensional scaling) which combines aspects of an "analytic" solution with an approach using loss functions is presented. (Author/JKS)

Detailed reanalyses of data reported in Studies in Educational Evaluation: Monograph No. 1 by Y. Kashti and Monograph No. 5 by U. Kattmann, 1979, were performed using an explicitly structurally oriented approach via target analysis (PINDIS). Results contradict those reached by Kashti and Kattmann. (RL)

The increasing use of multidimensional scaling (MDS) as a descriptive and explanatory aid to studying the behavior of individuals to complex stimuli raises some important theoretical questions regarding the interpretation that can be placed on such solutions. Problems involved in equating multidimensional scaling solutions with cognitive…

The monotone regression function of Kruskal and the rank image of Guttman and Lingoes are fitted to bivariate normal samples and their statistical properties contrasted. Tables of results are presented. (Author/JKS)

A method of optimal scaling for multivariate ordinal data--OSMOD--is described, within a generalized principal component analysis. It yields a: multidimensional configuration of items, unidimensional scale of category weights for each item, and multidimensional configuration of subjects. OSMOD involves solving an eigenvalue problem and executing a…

A full-information item factor analysis model for multidimensional polytomously scored item response data is developed as an extension of previous work by several authors. The model is expressed in factor-analytic and item response theory parameters, and an EM algorithm for estimation of the model parameters is presented. (SLD)