Descriptor
Cluster Analysis | 11 |
Cluster Grouping | 11 |
Multidimensional Scaling | 11 |
Citations (References) | 3 |
Comparative Analysis | 3 |
Correlation | 3 |
Matrices | 3 |
Factor Analysis | 2 |
Graphs | 2 |
Tables (Data) | 2 |
Academic Libraries | 1 |
More ▼ |
Source
Journal of the American… | 3 |
Educational and Psychological… | 1 |
Journal of Academic… | 1 |
Journal of Educational… | 1 |
Journal of Educational and… | 1 |
Multivariate Behavioral… | 1 |
Author
Dunn-Rankin, Peter | 1 |
Free, Spencer M. | 1 |
Kim, Moonja Park | 1 |
Marden, John I. | 1 |
May, William H. | 1 |
McCain, Katherine W. | 1 |
McGrath, William E. | 1 |
Miyamoto, S. | 1 |
Nakayama, K. | 1 |
Noma, Elliot | 1 |
Overall, John E. | 1 |
More ▼ |
Publication Type
Reports - Research | 8 |
Journal Articles | 6 |
Speeches/Meeting Papers | 2 |
Information Analyses | 1 |
Numerical/Quantitative Data | 1 |
Reports - General | 1 |
Education Level
Audience
Media Staff | 1 |
Practitioners | 1 |
Researchers | 1 |
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating

Tzeng, Oliver C. S.; May, William H. – Educational and Psychological Measurement, 1979
A strategy for reordering the hierarchical tree structure is presented. While the order of terminal nodes of Johnson's procedure is arbitrary, this procedure will rearrange every triad of nodes under a common least upper node so that the middle node is nonarbitrarily closest to the anchored node. (Author/CTM)
Descriptors: Cluster Analysis, Cluster Grouping, Matrices, Multidimensional Scaling

Overall, John E.; Free, Spencer M. – Journal of Educational and Psychological Measurement, 1974
Descriptors: Cluster Analysis, Cluster Grouping, Computer Programs, Multidimensional Scaling

Roussos, Louis A.; Stout, William F.; Marden, John I. – Journal of Educational Measurement, 1998
Introduces a new approach for partitioning test items into dimensionally distinct item clusters. The core of this approach is a new item-pair conditional-covariance-based proximity measure that can be used with hierarchical cluster analysis. The procedure can correctly classify, on average, over 90% of the items for correlations as high as 0.9.…
Descriptors: Cluster Analysis, Cluster Grouping, Correlation, Multidimensional Scaling
Dunn-Rankin, Peter; And Others – 1981
Measuring object similarity using the method of free clustering is gaining in popularity. Instructions are usually simple and since no structure is imposed on the subject's selection, response bias is reduced. More importantly, measures of object similarity derived from the judges' clustering can be adequately analyzed by the methods of…
Descriptors: Cluster Analysis, Cluster Grouping, Computer Oriented Programs, Mathematical Formulas

Noma, Elliot – Journal of the American Society for Information Science, 1984
Argues that co-citation methods combine citing behavior of authors by assuming they share common view of scientific literature which affects assessments of dimensionality and clustering of articles. Co-citation matrices, effects of shared point-of-view assumption, and co-citation compared with bibliographic coupling and centroid scaling are…
Descriptors: Bibliographic Coupling, Citations (References), Cluster Analysis, Cluster Grouping

McCain, Katherine W. – Journal of the American Society for Information Science, 1984
Author cocitation analysis was used to investigate changes in intellectual structure of macroeconomics over two consecutive time periods, 1972-1977 and 1978-1983. Profile analysis, nonmetric multidimensional scaling, and clustering techniques were used to create two-dimensional maps displaying changing relationships among 41 authors as perceived…
Descriptors: Authors, Citations (References), Cluster Analysis, Cluster Grouping

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

Miyamoto, S.; Nakayama, K. – Journal of the American Society for Information Science, 1983
A method of two-stage clustering of literature based on citation frequency is applied to 5,065 articles from 57 journals in environmental and civil engineering. Results of related methods of citation analysis (hierarchical graph, clustering of journals, multidimensional scaling) applied to same set of articles are compared. Ten references are…
Descriptors: Algorithms, Citations (References), Civil Engineering, Cluster Analysis

Rosenberg, Seymour; Kim, Moonja Park – Multivariate Behavioral Research, 1975
Compares two basic variants of the sorting method: single-sort and multiple sort. The nature of individual differences in sorting, as well as sex differences, were also investigated. Stimulus materials were the 15 mutually exclusive kinship terms selected by Wallace and Atkins (1960). (RC)
Descriptors: Classification, Cluster Analysis, Cluster Grouping, College Students

McGrath, William E. – Journal of Academic Librarianship, 1986
Discusses the issue of centralization or decentralization of academic library collections, and describes a statistical analysis of book circulation at the University of Southwestern Louisiana that yielded subject area clusters as a compromise solution to the problem. Applications of the cluster model for all types of library catalogs are…
Descriptors: Academic Libraries, Centralization, Cluster Analysis, Cluster Grouping
Sirotnik, Kenneth A. – 1979
This report contains accounts of studies, about scales to be used in the "A Study of Schooling" research project, undertaken to derive indices for constructs presumed to be measureable by composites of items. The report is introduced by a discussion on the rationale for selecting the research methodology used and an explanation of the…
Descriptors: Behavioral Science Research, Cluster Analysis, Cluster Grouping, Correlation