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| Gorman, Bernard S. | 1 |
| Hubert, Lawrence | 1 |
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| McQuitty, Louis L. | 1 |
| Primavera, Louis H. | 1 |
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| Shepard, Roger N. | 1 |
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Hubert, Lawrence; Schultz, James – 1975
An empirical assesssment of the space distortion properties of two prototypic hierarchical clustering procedures is given in terms of an occupancy model developed from combinatorics. Using one simple example, the single-link and complete-link clustering strategies now in common use in the behavioral sciences are empirically shown to be space…
Descriptors: Behavioral Sciences, Classification, Cluster Analysis, Cluster Grouping
Peer reviewedMcQuitty, Louis L.; Koch, Valerie L. – Educational and Psychological Measurement, 1976
A relatively reliable and valid hierarchy of clusters of objects is plotted from the highest column entries, exclusively, of a matrix of interassociations between the objects. Having developed out of a loose definition of types, the method isolates both loose and highly definitive types, and all those in between. (Author/RC)
Descriptors: Cluster Analysis, Cluster Grouping, Comparative Analysis, Data Analysis
Peer reviewedGorman, Bernard S.; Primavera, Louis H. – Journal of Experimental Education, 1983
Factor and cluster analyses are distinctly different multivariate procedures with different goals. However, when used in a complementary fashion, each set of methods can be used to enhance the interpretation of results found in the other set of methods. Simple examples illustrating the joint use of the methods are provided. (Author)
Descriptors: Cluster Analysis, Correlation, Data Analysis, Factor Analysis
Peer reviewedShepard, Roger N. – Psychometrika, 1974
Six major problems confronting attempts to use nonmetric multidimensional scaling to represent structures underlying similarity data are identified and the author's prospects for over-coming each of these problems are presented. (RC)
Descriptors: Cluster Analysis, Comparative Analysis, Data Analysis, Goodness of Fit


