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Cited by 187

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Replicating Cluster Analysis: Method, Consistency, and Validity

Breckenridge, James N.·1989·Multivariate Behavioral Research

Abstract

To replicate a cluster analysis, clusters must first be described in terms of an objective classification rule. The effectiveness of three rules (nearest neighbor classification, nearest centroid assignment, and quadratic discriminant analysis) for replicating Ward's algorithm (Ward, 1963) is evaluated by Monte Carlo study. Consistent replication links clusters and their replicas identically over alternative cross-validation sequences (i.e., A replicates B, B replicates A) and is associated with recovery of known clusters. Replication using nearest neighbor classification results in superior goodness-of-fit, more frequent consistent replication, and significant prediction of recovery. Although moderate or greater replication dentoes good recovery, replication is not a necessary condition of recovery of true clusters.

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Metadata

Authors
Breckenridge, J. N.
Venue
Multivariate Behavioral Research
Published
1989-04
Volume
24
Issue
2
Pages
147-161
ISSN
  • 0027-3171 (ISSN-L)
  • 1532-7906
OpenAlex
W2052946386
Cited by
187
References
2
FWCI
1.49
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Replicating Cluster Analysis: Method, Consistency, and Validity. https://app.cochat.ai/papers/10.1207/s15327906mbr2402_1
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Breckenridge, J. N. (1989). Replicating Cluster Analysis: Method, Consistency, and Validity. Multivariate Behavioral Research. https://doi.org/10.1207/s15327906mbr2402_1

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