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Peer reviewedBurton, 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
PDF pending restorationMiller, Brent C.; Olson, David H. – 1976
The present study focuses on multiple dimensions of face-to-face marriage interaction as the basis for identifying patterns or "types" of couple relating. The research assumes that it is possible to classify marriage relationships by criteria which are objective enough to allow replication and concensus. Particular emphasis is placed on the…
Descriptors: Classification, Cluster Analysis, Data Analysis, Interaction Process Analysis
Morris, Theodore Allan – Proceedings of the ASIST Annual Meeting, 2002
Uses co-occurrence analysis of INSPEC classification codes and thesaurus terms assigned to medical informatics (biomedical information) journal articles and proceedings papers to reveal a more complete perspective of how information science and information technology (IS/IT) authors view medical informatics. Discusses results of cluster analysis…
Descriptors: Biomedicine, Classification, Cluster Analysis, Information Science
Peer reviewedRosenberg, 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
Peer reviewedBorner, Katy; Chen, Chaomei; Boyack, Kevin W. – Annual Review of Information Science and Technology (ARIST), 2003
Reviews visualization techniques for scientific disciplines and information retrieval and classification. Highlights include historical background of scientometrics, bibliometrics, and citation analysis; map generation; process flow of visualizing knowledge domains; measures and similarity calculations; vector space model; factor analysis;…
Descriptors: Bibliometrics, Classification, Cluster Analysis, Factor Analysis
Peer reviewedGliner, Gail S. – School Science and Mathematics, 1989
Examines the students' understanding of mathematical structure and the relationship between problem solving and the identification of the structure in 13 word problems. Multidimensional scaling and hierarchical cluster analysis were used to assess how subjects organized word problems in their minds. (YP)
Descriptors: Classification, Cluster Analysis, College Mathematics, Mathematical Applications
Fisher, Mark A. – 1992
A model of graph comprehension is proposed including perceptual and memory processes. Multidimensional scaling (MDS), cluster analysis, and analysis of variance (ANOVA) were used to determine how college students with different mathematical experience read different types of bar graphs. Data were collected at the University of Oklahoma (Norman)…
Descriptors: Analysis of Variance, Classification, Cluster Analysis, College Students
