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Suziedelis, Antanas; And Others – Multivariate Behavioral Research, 1976
A method of typological analysis was applied to computer-generated 96-item questionnaire data for 100 cases, under a variety of conditions to analyze both the item-level and score-level. The results showed a considerable advantage of score-level approach in the number, size, and replicability of clusters recovered. (DEP)
Descriptors: Classification, Cluster Analysis, Cluster Grouping, Comparative Analysis

McQuitty, 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

Schweizer, Karl – Multivariate Behavioral Research, 1992
Two versions of a decision rule for determining the most appropriate number of clusters on the basis of a correlation matrix are presented, applied, and compared with three other decision rules. The new rule is efficient for determining the number of clusters on the surface level for multilevel data. (SLD)
Descriptors: Cluster Analysis, Cluster Grouping, Comparative Analysis, Correlation

McCain, Katherine W. – Journal of the American Society for Information Science, 1986
To test validity of cocitation studies as representations of intellectual structure, five-six years of aggregate cocitation data for 41 authors in macroeconomics and 49 authors in genetics of fruit flies were compared with independent judgments of interauthor similarity collected from 14 macroeconomists and 15 geneticists via a card-sorting…
Descriptors: Authors, Charts, Citations (References), Cluster Analysis

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

Shaw, W. M., Jr. – Information Processing and Management, 1993
Describes a study conducted on the cystic fibrosis (CF) database, a subset of MEDLINE, that investigated clustering structure and the effectiveness of cluster-based retrieval as a function of the exhaustivity of the uncontrolled subject descriptions. Results are compared to calculations for controlled descriptions based on Medical Subject Headings…
Descriptors: Bibliographic Records, Cluster Analysis, Cluster Grouping, Comparative Analysis

Griffiths, Alan; And Others – Journal of the American Society for Information Science, 1986
Reports on comparative study of document classifications produced by use of single linkage, complete linkage, group average, and Ward clustering methods. Findings of work that compares use of clusters consisting of pairs of documents with conventional best match searches are also reported. Thirty-four references are provided. (EJS)
Descriptors: Cluster Analysis, Cluster Grouping, Comparative Analysis, Information Retrieval

Griffiths, Alan; And Others – Journal of Documentation, 1984
Considers classifications produced by application of single linkage, complete linkage, group average, and word clustering methods to Keen and Cranfield document test collections, and studies structure of hierarchies produced, extent to which methods distort input similarity matrices during classification generation, and retrieval effectiveness…
Descriptors: Algorithms, Classification, Cluster Analysis, Cluster Grouping

Terenzini, Patrick T.; And Others – Research in Higher Education, 1980
A methodology developed as an alternative to conventional institutional classification structures, intended to reduce the limitations of those models, is described. Ways in which the methodology can be used for planning, administrative, and research purposes are discussed, as are the dangers in using "peer groups" for institutional…
Descriptors: Classification, Cluster Analysis, Cluster Grouping, College Planning

Denney, Nancy Wadsworth; Ziobrowski, Martin – Journal of Experimental Child Psychology, 1972
Study suggests that, rather than being less able to organize information, young children simply organize according to different criteria than adults. (Authors)
Descriptors: Age Differences, Cluster Analysis, Cluster Grouping, College Students

Yerkey, A. Neil – Journal of the American Society for Information Science, 1983
This study attempts to analyze descriptors taken from subject categories in ERIC thesaurus and used as search terms on CROSS database Bibliographic Retrieval Services. An expectation ratio was computed and cluster analysis was conducted to discover subject relationships among databases. A list of databases retrieved and 12 references are appended.…
Descriptors: Cluster Analysis, Cluster Grouping, Comparative Analysis, Data Analysis