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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
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ten Berge, Jos M. F. – Psychometrika, 1991
A globally optimal solution is presented for a class of functions composed of a linear regression function and a penalty function for the sums of squared regression weights. A completing-the-squares approach is used, rather than calculus, because it yields global minimality easily in two of three cases examined. (SLD)
Descriptors: Algorithms, Equations (Mathematics), Mathematical Models, Matrices
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Rodgers, Joseph Lee; Thompson, Tony D. – Applied Psychological Measurement, 1992
A flexible data analysis approach is proposed that combines the psychometric procedures seriation and multidimensional scaling. The method, which is particularly appropriate for analysis of proximities containing temporal information, is illustrated using a matrix of cocitations in publications by 18 presidents of the Psychometric Society.…
Descriptors: Citations (References), Cluster Analysis, Mathematical Models, Matrices
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
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Reynolds, 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
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Zielman, Berrie; Heiser, Willem J. – Psychometrika, 1993
An algorithm based on the majorization theory of J. de Leeuw and W. J. Heiser is presented for fitting the slide-vector model. It views the model as a constrained version of the unfolding model. A three-way variant is proposed, and two examples from market structure analysis are presented. (SLD)
Descriptors: Algorithms, Classification, Equations (Mathematics), Estimation (Mathematics)
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Weeks, David G.; Bentler, P.M. – Psychometrika, 1982
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)
Descriptors: Bibliographic Coupling, Data Analysis, Mathematical Models, Matrices
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Krus, David J. – Applied Psychological Measurement, 1978
The Cartesian theory of dimensionality (defined in terms of geometric distances between points in the test space) and Leibnitzian theory (defined in terms of order-generative connected, transitive, and asymmetric relations) are contrasted in terms of the difference between a factor analysis and an order analysis of the same data. (Author/CTM)
Descriptors: Factor Analysis, Mathematical Models, Matrices, Multidimensional Scaling
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Bart, William M. – Applied Psychological Measurement, 1978
Two sets of five items each from the Law School Admission Test were analyzed by two methods of factor analysis, and by the Krus-Bart ordering theoretic method of multidimensional scaling. The results indicated a conceptual gap between latent trait theoretic procedures and order theoretic procedures. (Author/CTM)
Descriptors: Factor Analysis, Higher Education, Mathematical Models, Matrices
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Pham, Tuan Dinh; Mocks, Joachim – Psychometrika, 1992
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)
Descriptors: Equations (Mathematics), Estimation (Mathematics), Factor Analysis, Least Squares Statistics
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Rudnitsky, Alan N. – 1977
Three approaches to the graphic representation of similarity and dissimilarity matrices are compared and contrasted. Specifically, Kruskal's multidimensional scaling, Johnson's hierarchical clustering, and Waern's graphing techniques are employed to depict, in two dimensions, data representing the structure of a set of botanical concepts. Each of…
Descriptors: Botany, Cluster Analysis, Cluster Grouping, Comparative Analysis
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Jackson, Douglas N.; Helmes, Edward – Applied Psychological Measurement, 1979
A basic structure approach is proposed for obtaining multidimensional scale values for attitude, achievement, or personality items from response data. The technique permits the unconfounding of scale values due to response bias and content and partitions item indices of popularity or difficulty among a number of relevant dimensions. (Author/BH)
Descriptors: Higher Education, Interest Inventories, Item Analysis, Mathematical Models
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Kloot, Willem A. van der; Herk, Hester van – Multivariate Behavioral Research, 1991
Two sets of real sorting data from 50 college students are used to compare results of multidimensional scaling of raw co-occurrence frequencies or dissimilarity measures (D) and profile distances (delta) to determine which yields a better representation of the underlying structure of 2 sets of stimuli. Slight differences are discussed. (SLD)
Descriptors: Classification, Cognitive Processes, College Students, Comparative Analysis
Jones, Patricia B.; And Others – 1987
In order to determine the effectiveness of multidimensional scaling (MDS) in recovering the dimensionality of a set of dichotomously-scored items, data were simulated in one, two, and three dimensions for a variety of correlations with the underlying latent trait. Similarity matrices were constructed from these data using three margin-sensitive…
Descriptors: Cluster Analysis, Correlation, Difficulty Level, Error of Measurement
Sireci, Stephen G.; Geisinger, Kurt – 1993
Various methods used to assess the content of a test are reviewed, and a new procedure designed to improve on these methods is presented. The two tests considered are a professional licensure examination, the auditing section of the Uniform Certified Public Accountant Examination, and an educational achievement test, a nationally standardized…
Descriptors: Achievement Tests, Certified Public Accountants, Cluster Analysis, Content Analysis