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Van Deun, Katrijn; Heiser, Willem J.; Delbeke, Luc – Multivariate Behavioral Research, 2007
A multidimensional unfolding technique that is not prone to degenerate solutions and is based on multidimensional scaling of a complete data matrix is proposed: distance information about the unfolding data and about the distances both among judges and among objects is included in the complete matrix. The latter information is derived from the…
Descriptors: Multidimensional Scaling, Correlation, Simulation, Computer Software
Culpepper, Steven Andrew – Multivariate Behavioral Research, 2009
This study linked nonlinear profile analysis (NPA) of dichotomous responses with an existing family of item response theory models and generalized latent variable models (GLVM). The NPA method offers several benefits over previous internal profile analysis methods: (a) NPA is estimated with maximum likelihood in a GLVM framework rather than…
Descriptors: Profiles, Item Response Theory, Models, Maximum Likelihood Statistics
Kim, Se-Kang; Davison, Mark L.; Frisby, Craig L. – Multivariate Behavioral Research, 2007
This paper describes the Confirmatory Factor Analysis (CFA) parameterization of the Profile Analysis via Multidimensional Scaling (PAMS) model to demonstrate validation of profile pattern hypotheses derived from multidimensional scaling (MDS). Profile Analysis via Multidimensional Scaling (PAMS) is an exploratory method for identifying major…
Descriptors: Profiles, Factor Analysis, Multidimensional Scaling, Evaluation Methods

Tsogo, L.; Masson, M. H.; Bardot, Anne – Multivariate Behavioral Research, 2000
Presents main similarity task methods available for scaling a large objects set and reviews their practicality. Discusses ways to increase the efficiency of the similarity task while maintaining satisfactory scaling solutions. Notes that the choice of appropriate task first depends on the kind of objects of stimuli being scaled. (SLD)
Descriptors: Multidimensional Scaling, Research Methodology

Meara, Kevin; Robin, Frederic; Sireci, Stephen G. – Multivariate Behavioral Research, 2000
Investigated the usefulness of multidimensional scaling (MDS) for assessing the dimensionality of dichotomous test data. Focused on two MDS proximity measures, one based on the PC statistic (T. Chen and M. Davidson, 1996) and other, on interitem Euclidean distances. Simulation results show that both MDS procedures correctly identify…
Descriptors: Correlation, Multidimensional Scaling, Simulation, Test Items

Jones, Russell A.; And Others – Multivariate Behavioral Research, 1978
Values were elicited spontaneously from a sample of undergraduates and adults attending college, and were compared to Rokeach's terminal and instrumental values. Multidimensional scaling revealed a simpler structure among spontaneously mentioned values than Rokeach's values. (JKS)
Descriptors: College Students, Higher Education, Multidimensional Scaling, Values

Levine, David M. – Multivariate Behavioral Research, 1977
Nonmetric multidimensional scaling and hierarchical clustering procedures are applied to a confusion matrix of numerals. Two dimensions were interpreted: straight versus curved, and locus of curvature. Four major clusters of numerals were developed. (Author/JKS)
Descriptors: Cluster Analysis, Information Processing, Multidimensional Scaling, Numbers

Simmen, Martin W. – Multivariate Behavioral Research, 1996
Several methodological issues in the multidimensional scaling of coarse dissimilarities were studied, examining whether it was better to scale dissimilarity data directly or to scale a new matrix derived from the original by row comparisons. Findings support an alternative row-comparison measure based on the Jacard coefficient. (SLD)
Descriptors: Comparative Analysis, Matrices, Multidimensional Scaling, Research Methodology

Burton, Michael L. – Multivariate Behavioral Research, 1975
Three dissimilarity measures for the unconstrained sorting task are investigated. All three are metrics, but differ in the kind of compensation which they make for differences in the sizes of cells within sortings. Empirical tests of the measures are done with sorting data for occupations names and the names of behaviors, using multidimensional…
Descriptors: Classification, Cluster Analysis, Correlation, Matrices

Sjoberg, Lennart – Multivariate Behavioral Research, 1975
An analysis of preferences with respect to silhouette drawings of nude females is presented. Systematic intransitivities were discovered. The dispersions of differences (comparatal dispersons) were shown to reflect the multidimensional structure of the stimuli, a finding expected on the basis of prior work. (Author)
Descriptors: Correlation, Dimensional Preference, Multidimensional Scaling, Psychological Patterns

Fenker, Richard; Tees, Sandra – Multivariate Behavioral Research, 1976
About 92 percent of the children studied had stable, organized cognitive structures for the experimental stimuli while an analysis of the sorting data indicated that only 30 percent of the children had stable structures. (Author/DEP)
Descriptors: Cognitive Processes, Multidimensional Scaling, Preschool Children, Psychomotor Skills

Bijmolt, Tammo H. A.; DeSarbo, Wayne S.; Wedel, Michel – Multivariate Behavioral Research, 1998
A multidimensional scaling procedure is introduced that attempts to derive a spatial representation of stimuli unconfounded by the effect of subjects' degrees of familiarity with these stimuli. A Monte Carlo study investigating the extent to which the procedure recovers known parameters shows that the procedure succeeds in adjusting for…
Descriptors: Familiarity, Models, Monte Carlo Methods, Multidimensional Scaling
Kim, Se-Kang; Frisby, Craig L.; Davison, Mark L. – Multivariate Behavioral Research, 2004
Two of the most popular methods of profile analysis, cluster analysis and modal profile analysis, have limitations. First, neither technique is adequate when the sample size is large. Second, neither method will necessarily provide profile information in terms of both level and pattern. A new method of profile analysis, called Profile Analysis via…
Descriptors: Profiles, Multidimensional Scaling, Cognitive Style, Scores

Lund, Thorleif – Multivariate Behavioral Research, 1975
An alternative content method, allowing bipolar representation and based on separate scaling of quality and intensity, is presented. For comparative purposes the method was used together with a distance method and an ordinary content method, with nine words denoting emotions as stimuli. (Author)
Descriptors: Comparative Analysis, Factor Analysis, Multidimensional Scaling, Psychological Patterns

Jones, Russell A.; And Others – Multivariate Behavioral Research, 1989
The stability of dimensions extracted from a body of free response data was studied using 1,523 expressions of concern and questions raised by 271 elderly persons and analyzed by 2 groups of experimenters. The structures of resulting multidimensional configurations obtained by the 2 groups were identical. (SLD)
Descriptors: Data Analysis, Hypothesis Testing, Multidimensional Scaling, Older Adults