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Sak, Ugur – Roeper Review, 2009
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…
Descriptors: Academically Gifted, Factor Analysis, Psychometrics, Ability Identification
Peer reviewedDegerman, Richard – Perceptual and Motor Skills, 1981
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)
Descriptors: Mathematical Models, Multidimensional Scaling, Multivariate Analysis
Peer reviewedBatagelj, Vladimir – Psychometrika, 1981
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)
Descriptors: Cluster Analysis, Mathematical Models, Multidimensional Scaling
Peer reviewedMullen, Kenneth; Ennis, Daniel M. – Psychometrika, 1987
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)
Descriptors: Mathematical Models, Monte Carlo Methods, Multidimensional Scaling
Peer reviewedTakane, Yoshio; Carroll, J. Douglas – Psychometrika, 1981
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)
Descriptors: Mathematical Models, Maximum Likelihood Statistics, Multidimensional Scaling
Peer reviewedDunn, Terrence R.; Harshman, Richard A. – Psychometrika, 1982
The kinds of individual differences in perceptions permitted by the weighted euclidean model for multidimensional scaling are more restrictive than those allowed by models developed by Tucker or Carroll. It is shown how problems which occur when using the more general models can be removed. (Author/JKS)
Descriptors: Data Analysis, Individual Differences, Mathematical Models, Multidimensional Scaling
Peer reviewedBorg, Ingiver; Lingoes, James C. – Psychometrika, 1980
A method for externally constraining certain distances in multidimensional scaling configurations is introduced and illustrated. The method is described in detail and several examples are presented. (Author/JKS)
Descriptors: Algorithms, Hypothesis Testing, Mathematical Models, Multidimensional Scaling
Peer reviewedLangeheine, Rolf – Studies in Educational Evaluation, 1980
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)
Descriptors: Comparative Analysis, Foreign Countries, Hypothesis Testing, Mathematical Models
Tanaka, J. S. – 1981
Using Goodman's (1975) notion of quasi-independence as a method of obtaining goodness of fit measures for non-scalable types in a scalogram analysis, archival data sets were examined using available Guttman scaling techniques, recent developments in latent structure analysis, and multidimensional scaling procedures. The Stouffer-Toby (1951) data…
Descriptors: Goodness of Fit, Mathematical Models, Multidimensional Scaling, Rating Scales
Gabriel, Roy M. – 1975
Multidimensional scaling (MDS) a highly reliable measurement technique, often requires an overwhelming task of the subject in the data collection procedure. This investigation was designed to determine the loss of precision in solution associated with five degrees of systematic reduction in the data collection task. Data were simulated via Monte…
Descriptors: Data Analysis, Data Collection, Mathematical Models, Matrices
Peer reviewedReynolds, Thomas J.; And Others – Psychometrika, 1987
An algorithm for assessing the correspondence of one or more attribute rating variables to a symmetric matrix of dissimilarities is presented. It is useful as an alternative to fitting property variables into a multidimensional scaling space. The relation between the matrix and the variables is determined by evaluating pairs of pairs relations.…
Descriptors: Mathematical Models, Matrices, Multidimensional Scaling, Predictor Variables
Peer reviewedTversky, Amos; Gati, Itamar – Psychological Review, 1982
The coincidence hypothesis predicts that dissimilarity between objects that differ on two separable dimensions is larger than predicted from their unidimensional differences on the basis of triangle inequality and segmental additivity. The coincidence hypothesis was supported in two-dimensional stimuli studies. (Author/CM)
Descriptors: Classification, Discriminant Analysis, Hypothesis Testing, Mathematical Models
Peer reviewedLingoes, James C.; Borg, Ingwer – Psychometrika, 1978
A family of models for the representation and assessment of individual differences for multivariate data called PINDIS (Procrustean Individual Differences Scaling) is presented. PINDIS sheds new light on the interpretability and applicability of a variety of multidimensional scaling models. (Author/JKS)
Descriptors: Computer Programs, Individual Differences, Mathematical Models, Multidimensional Scaling
Peer reviewedPsychometrika, 1981
A single-step maximum likelihood estimation procedure is developed for multidimensional scaling of dissimilarity data measured on rating scales. The procedure can fit the euclidian distance model to the data under various assumptions about category widths and under two distributional assumptions. Practical uses of the method are demonstrated.…
Descriptors: Computer Programs, Mathematical Models, Maximum Likelihood Statistics, Multidimensional Scaling
Peer reviewedDenison, Daniel R. – Multivariate Behavioral Research, 1982
Structural equation modeling is applied in conjunction with constrained monotone distance analysis. These alternative methods are used in an evaluation of a social-psychological model derived from Likert's theory of organizational behavior. (Author/JKS)
Descriptors: Data Analysis, Hypothesis Testing, Mathematical Models, Multidimensional Scaling

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