The classification capabilities of the one-dimensional Kohonen neural network (T. Kohonen, 1995) were compared with those of two partitioning and three hierarchical cluster methods in 2,580 data sets with known cluster structure. Overall, the performance of the Kohonen networks was similar to, or better than, that of the others. Implications for…

Scores on different items of a test are often combined linearly (sometimes with equal weights) to form the test score, mainly for the sake of computational convenience. In this paper, the author studies the consequences of doing this, and also studies the problems involved in finding a suitable linear combination. (Author/RK)

Describes an interactive procedure for multiobjective asymmetric unidimensional seriation problems that uses a dynamic-programming algorithm to generate partially the efficient set of sequences for small to medium-sized problems and a multioperational heuristic to estimate the efficient set for larger problems. Applies the procedure to an…

An Extended Two-Way Euclidean Multidimensional Scaling (MDS) model that assumes both common and specific dimensions is described and contrasted with the "standard" (Two-Way) MDS model. Illustrations with both artificial and real data on the judged similarity of nations are provided. (TJH)

Minimum trace factor analysis has been used to find the greatest lower bound to reliability. This technique, however, fails to be scale free. A solution to the scale problem is proposed through the maximization of the greatest lower bound as the function of weights. (Author/JKS)

The frequencies of "m" independent "p-way" contingency tables are analyzed by a model that assumes that the ordinal category data in each of "m" groups are generated from a latent continuous multivariate normal distribution. The model permits analysis of several groups of individuals simultaneously. (TJH)

A nonspatial operationalization of the Krumhansl distance-density model of similarity is presented. The conceptual model and empirical evidence are reviewed. A nonspatial, tree-fitting methodology is described, which is sufficiently flexible to fit several competing hypotheses of similarity formation. Extensions to spatial models, three-way…

An algorithm, based on a solution for C. I. Mosier's oblique Procrustes rotation problem, is presented for the best least-squares fitting correlation matrix approximating a given missing value or improper correlation matrix. Results are of interest for missing value and tetrachoric correlation, indefinite matrix correlation, and constrained…

A Monte Carlo simulation and applications to eight sets of proximity data are presented to support the practical utility of a network scaling algorithm (NETSCAL)--NETwork SCALing. The algorithm determines which vertices within a network are directly connected by an arc and estimates the length of each arc. (TJH)

The current state of multidimensional scaling using the city-block metric is reviewed, with attention to (1) substantive and theoretical issues; (2) recent algorithmic developments and their implications for analysis; (3) isometries with other metrics; (4) links to graph-theoretic models; and (5) prospects for future development. (SLD)

This paper offers a new methodology for analyzing individual differences in preference judgments with regard to a set of stimuli. (Author)

A probabilistic choice model, based on L. L. Thurstone's Law of Comparative Judgment Case V, is developed for paired comparisons data about psychological stimuli. The model assumes that each stimulus is measured on a small number of physical variables. An algorithm for estimating parameters is illustrated with real data. (SLD)

Discusses the different strategies employed by three practical nonmetric multidimensional scaling algorithms using Monte Carlo techniques. (Author/RK)

Some examinees' test-taking behavior may be so idiosyncratic that their test scores are not comparable to those of more typical examinees. A new theoretical approach to appropriateness measurement is proposed that specifies a likelihood ratio test and an efficient computer algorithm for computing the test statistic. (TJH)

A method is proposed for constructing a population covariance matrix as the sum of a particular model plus a nonstochastic residual matrix, with the stipulation that the model holds with a prespecified lack of fit. The procedure is considered promising for Monte Carlo studies. (SLD)