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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 reviewedStewart, Thomas R. – Multivariate Behavioral Research, 1974
Suggests a way of using factor analytic techniques to supplement multidimensional scaling in such a way as to provide a firm basis for evaluating multidimensional representations. (Author/RC)
Descriptors: Evaluation Criteria, Factor Analysis, Matrices, Multidimensional Scaling
Peer reviewedArabie, Phipps – Psychometrika, 1978
An examination is made concerning the utility and design of studies comparing nonmetric multidimensional scaling algorithms and their initial configurations, as well as the agreement between the results of such studies. Various practical details of nonmetric scaling are also considered. (Author/JKS)
Descriptors: Correlation, Goodness of Fit, Matrices, Monte Carlo Methods
Peer reviewedKrus, 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
Peer reviewedBart, 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
Peer reviewedNoma, Elliot; Smith, D. Randall – Multivariate Behavioral Research, 1985
Correspondence analysis can provide spatial or clustering representations by assigning spatial coordinates minimizing the distance between individuals linked by a sociometric relationship. These scales may then be used to identify individuals' locations in a multidimensional representation of a group's structure or to reorder the rows and columns…
Descriptors: Cluster Analysis, Goodness of Fit, Matrices, Multidimensional Scaling
Peer reviewedPeay, Edmund R. – Psychometrika, 1975
A class of closely related hierarchical grouping methods are discussed and a procedure which implements them in an integrated fashion is presented. These methods avoid some theoretical anomalies inherent in clustering and provide a framework for viewing partitioning and nonpartitioning grouping. Significant relationships between these methods and…
Descriptors: Classification, Cluster Grouping, Computer Programs, Data Analysis
Reynolds, Thomas J. – 1976
A method of factor extraction specific to a binary matrix, illustrated here as a person-by-item response matrix, is presented. The extraction procedure, termed ERGO, differs from the more commonly implemented dimensionalizing techniques, factor analysis and multidimensional scaling, by taking into consideration item difficulty. Utilized in the…
Descriptors: Discriminant Analysis, Factor Analysis, Item Analysis, Matrices
Peer reviewedJackson, 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
Ho, Andrew D.; Haertel, Edward H. – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2006
Problems of scale typically arise when comparing test score trends, gaps, and gap trends across different tests. To overcome some of these difficulties, we can express the difference between the observed test performance of two groups with graphs or statistics that are metric-free (i.e., invariant under positive monotonic transformations of the…
Descriptors: Testing Programs, Test Results, Comparative Testing, Multidimensional Scaling


