Application of methods of cluster analysis to data processing in psychological studies

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Abstract

The author describes the general provisions of the basic characteristics and goals of cluster analysis, and also conducts a comparative analysis of the most used methods of cluster analysis. The article presents standard methods implemented in the most commonly used statistical packages, their development and improvement and describe original methods that are not realized in statistical packages.

General Information

Keywords: multivariate data analysis, classification, cluster, models of latent groups, hierarchical agglomeration method, metrics, dendrogram, strategy of unification, distance matrix, iterative procedure, dendrite, evaluation of bound, associative and chain clusters, luster-collection, method of latent classes

Journal rubric: Mathematical Psychology

Article type: scientific article

For citation: Savchenko T.N. Application of methods of cluster analysis to data processing in psychological studies. Eksperimental'naâ psihologiâ = Experimental Psychology (Russia), 2010. Vol. 3, no. 2, pp. 67–86. (In Russ., аbstr. in Engl.)

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Information About the Authors

Tatyana N. Savchenko, PhD in Psychology, Associate Professor, Leading Researcher, Institute of Psychology of Russian Academy of Sciences, Moscow, Russia, ORCID: https://orcid.org/0000-0002-4301-5590, e-mail: t.n.savchenko@mail.ru

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