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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
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Pennell, Roger – Educational and Psychological Measurement, 1972
Author argues that simplistic and/or heuristic approaches to the Tucker and Messick model (an individual differences model for multidimensional scaling, 1963) are often inadequate. (Author/CB)
Descriptors: Data Analysis, Evaluation, Individual Differences, Mathematical Models
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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Denison, 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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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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Ramsay, J. O. – Psychometrika, 1980
In studies involving judgments of similarity or dissimilarity, a variety of other variables may also be measured. In such cases, there are important advantages to joint analyses of the dissimilarity and collateral variables. A variety of models are described for relating these and algorithms are described for fitting these to data. (Author/JKS)
Descriptors: Data Analysis, Guessing (Tests), Mathematical Models, Measurement Techniques
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Bechtel, Gordon G.; And Others – Psychometrika, 1971
Contains a solution for the multidimensional scaling of pairwise choice when individuals are represented as dimensional weights. The analysis supplies an exact least squares solution and estimates of group unscalability parameters. (DG)
Descriptors: Data Analysis, Mathematical Models, Measurement Techniques, Multidimensional Scaling
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Langeheine, Rolf – Psychometrika, 1982
The degree to which Procrustean Individual Differences Scaling can be extended to related topics such as target analysis is discussed and a Monte Carlo study investigating the fit of the model under various conditions is presented. (JKS)
Descriptors: Data Analysis, Goodness of Fit, Individual Differences, Mathematical Models
Peer reviewed Peer reviewed
And Others; Takane, Yoshio – Psychometrika, 1980
An individual differences additive model is discussed which represents individual differences in additivity by differential weighting or additive factors. A procedure for estimating model parameters for various data measurement characteristics is developed. The method is found to be very useful in describing certain types of developmental change…
Descriptors: Algorithms, Data Analysis, Least Squares Statistics, Mathematical Models
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Schonemann, Peter H.; And Others – Multivariate Behavioral Research, 1975
Descriptors: Algorithms, Data Analysis, Dimensional Preference, Individual Differences
Peer reviewed Peer reviewed
Levine, Joel H. – Psychometrika, 1979
Social and naturally occurring choice phenomena are often of the "pick any" type in which the number of choices made by a subject as well as the set of alternatives from which they are chosen is unconstrained. A model and scaling method for these data are introduced. (Author/JKS)
Descriptors: Data Analysis, Item Analysis, Mathematical Models, Multidimensional Scaling
Peer reviewed Peer reviewed
DeSarbo, Wayne S.; And Others – Psychometrika, 1992
TSCALE, a multidimensional scaling procedure based on the contrast model of A. Tversky for asymmetric three-way, two-mode proximity data, is presented. TSCALE conceptualizes a latent dimensional structure to describe the judgmental stimuli. A Monte Carlo analysis and two consumer psychology applications illustrate the procedure. (SLD)
Descriptors: Consumer Economics, Data Analysis, Equations (Mathematics), Mathematical Models
McKinley, Robert L.; Reckase, Mark D. – 1982
The usefulness of the general Rasch model for multidimensional data, from the most simple formulations to the more complex versions of the model, is explored. Also investigated was whether the parameters of the models could be readily interpreted. Models investigated included: (1) the vector model; (2) the product term model; (3) the vector and…
Descriptors: Data Analysis, Factor Analysis, Goodness of Fit, Latent Trait Theory
Peer reviewed Peer reviewed
Langeheine, Rolf – Studies in Educational Evaluation, 1978
A three-way multidimensional scaling model is presented as a method for identifying classroom cliques, by simultaneous analysis of three variables (for example, chooser/choosen/criteria). Two scaling models--Carroll and Chang's INDSCAL and Lingoes' PINDIS--are presented and applied to two sets of empirical data. (CP)
Descriptors: Classroom Environment, Classroom Research, Cluster Analysis, Computer Programs