The present study proposes and examines the multidimensional vector (MDV) model framework as a modeling schema for choice response times. MDV extends the Thurstonian model, as well as signal detection theory, to classification tasks by taking into account the influence of response properties on stimulus discrimination. It is capable of accounting…

This article describes the affordances of using clinical interviews with struggling mathematics learners to inform intervention and instruction. A case study of a fourth grade student, Danny, is presented to give an illustrative example of the complexity of the student's mathematical understandings in terms of place value. From the clinical…

Papini and Pellegrini (Papini, M. R., & Pellegrini, S. "Scaling relative incentive value in consummatory behavior." "Learning and Motivation", in press) observed that, within limits, the level of consummatory responding of rats exposed to incentive downshifts in the concentration of sucrose solutions was similar when the ratio of test/training…

In this study, psychometric properties of the test of the three-mathematical minds (M3) were investigated. The M3 test was developed based on a multidimensional conception of giftedness to identify mathematically talented students. Participants included 291 middle-school students. Data analysis indicated that the M3 had a 0.73 coefficient as a…

Restricted multidimensional scaling models, allowing constraints on parameters, are extended to the case of asymmetric data. Examples of several models are provided, using journal citation data. Possible extensions of the models are considered. (Author/JKS)

A review of existing techniques for the analysis of three-way data revealed that none were appropriate to the wide variety of data usually encountered in psychological research, and few were capable of both isolating common information and systematically describing individual differences. Such a model is developed and evaluated. (Author/JKS)

Ideal point discriminant analysis (IPDA) is proposed for the analysis of contingency tables of cross-classified data. Several data sets illustrate IPDA, which combines log-linear and dual scaling models to provide a spatial representation of row and column categories and allow statistical evaluation of various structural hypotheses about…

Defines a random effects diagonal metric multidimensional scaling model, gives its computational algorithms, describes researchers' experiences with these algorithms, and provides an illustration of the use of the model and algorithms. (Author/SLD)

This special issues describes multidimensional scaling (MDS), with emphasis on proximity and preference models. An introduction and six papers review statistical developments in MDS study design and scrutinize MDS research in four areas of application (consumer, social, cognitive, and vocational psychology). (SLD)

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…

The notion of multidimensional structure is discussed within the framework of an additive component model of multidimensional scaling, where a configuration is considered to be composed of disjoint subspaces, each one of which reflects variation due to a specific stimulus component. Empirical examples are given. (Author/BW)

The multivariate stochastic processes associated with the Marshall-Olkin multivariate exponential distribution are shown to be able to generate several models of similarity or preference data in the literature. (JKS)

Milligan presented the conditions that are required for a hierarchical clustering strategy to be monotonic, based on a formula by Lance and Williams. The statement of the conditions is improved and shown to provide necessary and sufficient conditions. (Author/GK)

Multivariate models for the triangular and duo-trio methods are described, and theoretical methods are compared to a Monte Carlo simulation. Implications are discussed for a new theory of multidimensional scaling which challenges the traditional assumption that proximity measures and perceptual distances are monotonically related. (Author/GDC)

A maximum likelihood procedure is developed for multidimensional scaling where similarity or dissimilarity measures are taken by such ranking procedures as the method of conditional rank orders or the method of triadic combinations. An example is given. (Author/JKS)