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 language | English (US) |
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Pages (from-to) | 247-277 |
Number of pages | 31 |
Journal | American Journal of Community Psychology |
Volume | 21 |
Issue number | 2 |
DOIs | |
State | Published - Apr 1993 |
Externally published | Yes |
Keywords
- cluster analysis
- community diversity
- heterogeneous samples
- social networks
ASJC Scopus subject areas
- Health(social science)
- Applied Psychology
- Public Health, Environmental and Occupational Health