Cluster analysis in community research: Epistemology and practice

Bruce D. Rapkin, Douglas A. Luke

Research output: Contribution to journalArticle

177 Scopus citations

Abstract

Cluster analysis refers to a family of methods for identifying cases with distinctive characteristics in heterogeneous samples and combining them into homogeneous groups. This approach provides a great deal of information about the types of cases and the distributions of variables in a sample. This paper considers cluster analysis as a quantitative complement to the traditional linear statistics that often characterize community psychology research. Cluster analysis emphasizes diversity rather than central tendency. This makes it a valuable tool for a wide range of familiar problems in community research. A number of these applications are considered here, including the assessment of change over time, network composition, network density, person-setting relationships, and community diversity. A User's Guide section is included, which outlines the major decisions involved in a basic cluster analyses. Despite difficulties associated with the identification of optimal cluster solutions, carefully planned, theoretically informed application of cluster analysis has much to offer community researchers.

Original languageEnglish (US)
Pages (from-to)247-277
Number of pages31
JournalAmerican Journal of Community Psychology
Volume21
Issue number2
DOIs
StatePublished - Apr 1 1993
Externally publishedYes

Keywords

  • cluster analysis
  • community diversity
  • heterogeneous samples
  • social networks

ASJC Scopus subject areas

  • Health(social science)
  • Applied Psychology
  • Public Health, Environmental and Occupational Health

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