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Koellner, Karen; Colsman, Melissa; Risley, Rachael – TEACHING Exceptional Children, 2011
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…
Descriptors: Intervention, Number Concepts, Grade 4, Response to Intervention
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

Clarkson, Douglas B.; Gonzalez, Richard – Psychometrika, 2001
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)
Descriptors: Algorithms, Mathematical Models, Multidimensional Scaling
Davison, Mark L.; Kim, Se-Kang; Ding, Shuai – 2001
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…
Descriptors: Mathematical Models, Multidimensional Scaling, Profiles, Scores

Degerman, 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

Batagelj, 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

Mullen, 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

Takane, 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

Nishisato, Shizuhiko; Arri, P. S. – Psychometrika, 1975
A modified technique of separable programming was used to maximize the squared correlation ratio of weighted responses to partially ordered categories. The technique employs a polygonal approximation to each single-variable function by choosing mesh points around the initial approximation supplied by Nishisato's method. Numerical examples were…
Descriptors: Algorithms, Linear Programing, Mathematical Models, Matrices

Lund, Thorleif – Psychometrika, 1975
Among the criticisms of Micko's Halo Model are: 1) it is too restrictive to fit empirical data, 2) it misrepresents unrelated percepts as bipolar structures, 3) it requires all dimensions to be bipolar, and 4) it causes the interpretations of orthogonality of factors and factor loadings to become problematic. (Author/BJG)
Descriptors: Mathematical Models, Multidimensional Scaling, Ratios (Mathematics), Research Problems

MacCallum, Robert C. – Psychometrika, 1977
The role of conditionality in the INDSCAL and ALSCAL multidimensional scaling procedures is explained. The effects of conditionality on subject weights produced by these procedures is illustrated via a single set of simulated data. Results emphasize the need for caution in interpreting subject weights provided by these techniques. (Author/JKS)
Descriptors: Individual Differences, Mathematical Models, Multidimensional Scaling, Statistical Analysis

Dunn, 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

van Buuren, Stef; Heiser, Willem J. – Psychometrika, 1989
A method based on homogeneity analysis (multiple correspondence analysis or multiple scaling) is proposed to reduce many categorical variables to one variable with "k" categories. The method is a generalization of the sum of squared distances cluster analysis problem to the case of mixed measurement level variables. (SLD)
Descriptors: Cluster Analysis, Mathematical Models, Multidimensional Scaling, Statistical Analysis

Krus, David J. – Educational and Psychological Measurement, 1977
Order analysis is discussed as a method for description of formal structures in multidimensional space. Its algorithm was derived using a combination of psychometric theory, formal logic theory, information theory, and graph theory concepts. The model provides for adjustment of its sensitivity to random variation. (Author/JKS)
Descriptors: Mathematical Models, Measurement, Multidimensional Scaling, Rating Scales

Davidson, J. A. – Psychometrika, 1972
Descriptors: Geometric Concepts, Mathematical Models, Multidimensional Scaling, Serial Ordering