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| Classification | 8 |
| Cluster Analysis | 8 |
| Discriminant Analysis | 8 |
| Cluster Grouping | 4 |
| Statistical Analysis | 3 |
| Adolescents | 1 |
| Behavior Patterns | 1 |
| Bibliographies | 1 |
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| Educational and Psychological… | 1 |
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| Breckenridge, James N. | 1 |
| Cochran, L. R. | 1 |
| Dougherty, Donna | 1 |
| Farrell, William T. | 1 |
| Hale, Robert L. | 1 |
| Houston, Sam | 1 |
| Linden, James D. | 1 |
| Marx, Thomas J. | 1 |
| Newberger, Eli H. | 1 |
| Rogers, Gil | 1 |
| Schmidt, Stephen R. | 1 |
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Peer reviewedHouston, Sam; Schmidt, Stephen R. – Journal of Experimental Education, 1987
A modified automatic interaction detector (MAID) was combined with discriminant analysis (DA) to form MAIDDA and to determine whether it might improve classification results over classical DA methods. Application of MAIDDA to the 1983 and 1984 Air Force Academy's graduating classes (N = 3,012) showed that it is a promising clustering technique.…
Descriptors: Classification, Cluster Analysis, College Graduates, Discriminant Analysis
Peer reviewedRogers, Gil; Linden, James D. – Educational and Psychological Measurement, 1973
Descriptors: Classification, Cluster Analysis, Cluster Grouping, Discriminant Analysis
Peer reviewedCochran, L. R. – Social Behavior and Personality, 1976
Adult subjects (N=10) were studied to determine whether inconsistent information about others produces more discrimination of people or leads to alternative ways of categorizing. Pretest-posttest indications indicated inconsistency produced more discrimination of others and alternative ways of categorizing others. (SBP)
Descriptors: Behavior Patterns, Classification, Cluster Analysis, Discriminant Analysis
Peer reviewedBreckenridge, 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
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
Peer reviewedTerenzini, 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
Peer reviewedHale, Robert L.; Dougherty, Donna – Journal of School Psychology, 1988
Compared the efficacy of two methods of cluster analysis, the unweighted pair-groups method using arithmetic averages (UPGMA) and Ward's method, for students grouped on intelligence, achievement, and social adjustment by both clustering methods. Found UPGMA more efficacious based on output, on cophenetic correlation coefficients generated by each…
Descriptors: Adolescents, Children, Classification, Cluster Analysis
Newberger, Eli H.; Marx, Thomas J. – 1982
Members of a group of hospitalized children under 4 years of age (48 under care for child abuse, 97 for accidents, 41 for failure to thrive, and 23 for ingestions) were matched individually on age, social class, and race with controls suffering from comparable acute medical conditions. A structured maternal and paternal interview yielded 63…
Descriptors: Child Abuse, Child Rearing, Classification, Cluster Analysis


