A stochastic multidimensional scaling procedure is presented for analysis of three-mode, three-way pick any/"J" data. The procedure fits both vector and ideal-point models and characterizes the effect of situations by a set of dimension weights. An application in the area of consumer psychology is discussed. (SLD)

Points of view analysis, as a way to deal with individual differences in multidimensional scaling, was largely supplanted by the weighted Euclidean model. It is argued that the approach deserves new attention, especially as a technique to analyze group differences. A streamlined and integrated process is proposed. (SLD)

Uncorrectable skew and heteroscedasticity are among the "lemons" of psychological data, yet many important variables naturally exhibit these properties. For scales with a lower and upper bound, a suitable candidate for models is the beta distribution, which is very flexible and models skew quite well. The authors present…

Illustrated is the power of multidimensional scaling in reducing a complex set of proximity measures to a simple geometric picture that shows the relationship among data objects. Methods are discussed for determining the number of dimensions needed to represent a set. (Author/DEP)

The purpose of this paper is to present a generalization of the concept of item difficulty to test items that measure more than one dimension. Three common definitions of item difficulty were considered: the proportion of correct responses for a group of individuals; the probability of a correct response to an item for a specific person; and the…

Models for multidimensional scaling use metric spaces with additive difference metrics. Two important properties of additive difference metrics are decomposability and intradimensional subtractivity. A prediction was derived from these properties and tested experimentally. Eleven non-psychology students were used as subjects. Rectangles varying in…

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…

Social and naturally occurring choice phenomena are often of the "pick any" type in which the number of choices made by a subject as well as the set of alternatives from which they are chosen is unconstrained. A model and scaling method for these data are introduced. (Author/JKS)

The consequences of using item response theory (IRT) item bias detecting procedures with multidimensional IRT item data are examined. Limitations in procedures for detecting item bias are discussed. (SLD)

TSCALE, a multidimensional scaling procedure based on the contrast model of A. Tversky for asymmetric three-way, two-mode proximity data, is presented. TSCALE conceptualizes a latent dimensional structure to describe the judgmental stimuli. A Monte Carlo analysis and two consumer psychology applications illustrate the procedure. (SLD)

Sufficient conditions are derived for the consistency and asymptotic normality of the least squares estimator of a trilinear decomposition model for multiway data analysis. The limiting covariance matrix is computed. (Author/SLD)

The aim of this paper is to explore the Rasch model as a criterion of test homogeneity. Two empirical studies are presented to demonstrate this usage. From these studies it is argued that statistical tests of item characteristic curve (ICC) slopes are not sufficient in testing for heterogeneity. Tests of equality of ICC's over groups of subject…