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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

Milligan, Glenn W.; Cooper, Martha C. – Multivariate Behavioral Research, 1986
Five external criteria were used to evaluate the extent of recovery of the true structure in a hierarchical clustering solution. The results of the study indicated that the Hubert and Arabie adjusted Rank index was best suited to the task of comparison across hierarchy levels. (Author/LMO)
Descriptors: Cluster Analysis, Cluster Grouping, Measurement Techniques, Statistical Studies

Spreen, Otfried; Haaf, Robert G. – Journal of Learning Disabilities, 1986
Test scores of two groups of learning disabled children (N=63 and N=96) were submitted to cluster analysis in an attempt to replicate previously described subtypes. All three subtypes (visuo-perceptual, linguistic, and articulo-graphomotor types) were identified along with minimally and severely impaired subtypes. Similar clusters in the same…
Descriptors: Cluster Analysis, Cluster Grouping, Learning Disabilities, Longitudinal Studies

Halff, Henry M. – 1975
Graphical methods for evaluating the fit of Johnson's hierarchical clustering schemes are presented together with an example. These evaluation methods examine the extent to which the clustering algorithm can minimize the overlap of the distributions of intracluster and intercluster distances. (Author)
Descriptors: Classification, Cluster Analysis, Cluster Grouping, Graphs
Crandall, R. E. – 1973
In this study assumptions are made concerning the amount of clustering in sequences containing runs of equivalent elements. It is assumed that any valid clustering measure is linear with respect to union of runs and monotone increasing under iterations of clustering operators. With these two assumptions it follows that any such measure is of…
Descriptors: Cluster Analysis, Cluster Grouping, Data Analysis, Measurement Techniques

Levine, Marilyn M.; Levine, Leonard P. – Information Processing and Management, 1984
Presents system for automatic handling of ordered sets, states based on these sets, and differing points of view regarding Universe of Discourse. Aspects are represented by new logical "overlap" function with examples taken from Ranganathan's horse and carriage parable and several books involving four main concepts (history, geography,…
Descriptors: Cluster Analysis, Cluster Grouping, Diagrams, Information Retrieval

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
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
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
Cunningham, J. W.; And Others – 1974
The study explored the feasibility of deriving an educationally relevant occupational cluster structure based on Occupational Analysis Inventory (OAI) work dimensions. A hierarchical cluster analysis was applied to the factor score profiles of 814 occupations on 22 higher-order OAI work dimensions. From that analysis, 73 occupational clusters were…
Descriptors: Classification, Cluster Analysis, Cluster Grouping, Literature Reviews

Bergman, Lars R. – Multivariate Behavioral Research, 1988
When performing a classification study, it is often useful to leave a residue of unclassified entities to be analyzed separately. Using an interactional paradigm, theoretical reasoning for this approach is outlined. A procedure--RESIDAN--for conducting a classification analysis using a residue is described, and empirical data are provided. (TJH)
Descriptors: Classification, Cluster Analysis, Cluster Grouping, Error of Measurement

Breckenridge, James N. – Multivariate Behavioral Research, 1989
A Monte Carlo study evaluated the effectiveness of three rules of classifying objects into clusters: nearest neighbor classification; nearest centroid assignment; and quadratic discriminant analysis. Results suggest that the nearest neighbor rule is a useful tool for assessing the validity of the clustering procedure of J. H. Ward (1963). (SLD)
Descriptors: Classification, Cluster Analysis, Cluster Grouping, Discriminant Analysis
Ambrosino, Robert J.; And Others – 1974
Two studies were undertaken to demonstrate the usefulness of partitioning procedures for studying test items. Achievement test items in five content areas of educational measurement were used as stimuli to be sorted by groups of students with varying levels of sophistication with the content, with the hypothesis that sorting by classes with…
Descriptors: Achievement Tests, Classification, Cluster Analysis, Cluster Grouping
Farrell, William T. – 1975
"Classification: Purposes, Principles, Progress, Prospects" by Robert R. Sokal is reprinted in this document. It summarizes the principles of classification and cluster analysis in a manner which is of specific value to the Marine Corps Office of Manpower Utilization. Following the article is a 184 item bibliography on cluster analysis…
Descriptors: Bibliographies, Classification, Cluster Analysis, Cluster Grouping

Rescorla, Leslie – Journal of Autism and Developmental Disorders, 1988
Cluster analysis on factor analytic symptom profiles obtained from the Achenbach Child Behavior Checklist for 204 three- to five-year-old boys including 79 autistic and autistic-like children identified an autistic group as soon as three clusters were formed. This autistic cluster was later subdivided according to presence/absence of anxiety and…
Descriptors: Anxiety, Autism, Behavior Rating Scales, Check Lists