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)

This study determined through psychophysical comparison of scaling data that speech naturalness judgments of stutterers and nonstutterers from audiovisual recordings form a metathetic (or qualitative) rather than prothetic (or quantitative) continuum. Both direct magnitude estimation and equal-appearing interval scaling were valid, but interval…

Multidimensional scaling was applied to Women-in-General (n=300) and Men-in-General (n=300) samples of the Strong Interest Inventory. Participants were matched on occupational title, obtaining two-dimensional solutions that demonstrated gender differences in the underlying structure of vocational interests. (SK)

A globally optimal solution is presented for a class of functions composed of a linear regression function and a penalty function for the sums of squared regression weights. A completing-the-squares approach is used, rather than calculus, because it yields global minimality easily in two of three cases examined. (SLD)

A method of testing semantic differential scales for bipolarity is developed using a new conception of bipolarity that does not require unidimensionality. Assessment of Fielder's Least Preferred Coworker instrument with 63 college student subjects using multidimensional scaling revealed its significant departures from bipolarity. (SLD)

A flexible data analysis approach is proposed that combines the psychometric procedures seriation and multidimensional scaling. The method, which is particularly appropriate for analysis of proximities containing temporal information, is illustrated using a matrix of cocitations in publications by 18 presidents of the Psychometric Society.…

Presents an approach to multidimensional unfolding that reduces the occurrence of degenerate solutions and conducts a Monte Carlo study to demonstrate the superiority of the new method to the ALSCAL and KYST nonmetric procedures for student preference data. (SLD)