Cluster analysis and related techniques in medical research

Mclachlan G.J. (1992) Cluster analysis and related techniques in medical research. Statistical Methods in Medical Research, 1 1: 27-48. doi:10.1177/096228029200100103

Author Mclachlan G.J.
Title Cluster analysis and related techniques in medical research
Journal name Statistical Methods in Medical Research   Check publisher's open access policy
ISSN 1477-0334
Publication date 1992-01-01
Sub-type Article (original research)
DOI 10.1177/096228029200100103
Open Access Status Not yet assessed
Volume 1
Issue 1
Start page 27
End page 48
Total pages 22
Language eng
Subject 2713 Epidemiology
2613 Statistics and Probability
3605 Health Information Management
Abstract In this paper we review methods of cluster analysis in the context of classifying patients on the basis of clinical and/or laboratory type observations. Both hierarchical and non-hierarchical methods of clustering are considered, although the emphasis is on the latter type, with particular attention devoted to the mixture likelihood-based approach. For the purposes of dividing a given data set into g clusters, this approach fits a mixture model of g components, using the method of maximum likelihood. It thus provides a sound statistical basis for clustering. The important but difficult question of how many clusters are there in the data can be addressed within the framework of standard statistical theory, although theoretical and computational difficulties still remain. Two case studies, involving the cluster analysis of some haemophilia and diabetes data respectively, are reported to demonstrate the mixture likelihood-based approach to clustering.
Q-Index Code C1
Institutional Status Unknown

Document type: Journal Article
Sub-type: Article (original research)
Collection: Scopus Import - Archived
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Citation counts: Scopus Citation Count Cited 66 times in Scopus Article | Citations
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Created: Tue, 13 Sep 2016, 12:48:49 EST by System User