The p-Median Model as a Tool for Clustering Psychological Data

Hans Friedrich Köhn, Douglas Steinley, Michael J. Brusco

Research output: Contribution to journalArticlepeer-review


The p-median clustering model represents a combinatorial approach to partition data sets into disjoint, nonhierarchical groups. Object classes are constructed around exemplars, that is, manifest objects in the data set, with the remaining instances assigned to their closest cluster centers. Effective, state-of-the-art implementations of p-median clustering are virtually unavailable in the popular social and behavioral science statistical software packages. We present p-median clustering, including a detailed description of its mechanics and a discussion of available software programs and their capabilities. Application to a complex structured data set on the perception of food items illustrates p-median clustering.

Original languageEnglish (US)
Pages (from-to)87-95
Number of pages9
JournalPsychological Methods
Issue number1
StatePublished - Mar 2010
Externally publishedYes


  • Lagrangian relaxation
  • cluster analysis
  • combinatorial data analysis
  • heuristics
  • p-median problem

ASJC Scopus subject areas

  • Psychology (miscellaneous)


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