A Two-Mode Clustering Method to Capture the Nature of the Dominant Interaction Pattern in Large Profile Data Matrices

J. Schepers, I. van Mechelen

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)

Abstract

Profile data abound in a broad range of research settings. Often it is of considerable theoretical importance to address specific structural questions with regard to the major pattern as included in such data. A key challenge in this regard pertains to identifying which type of interaction (double ordinal, mixed ordinal/disordinal, double disordinal) most adequately fits the major pattern in a profile data set at hand. In the present article a novel methodology is proposed to deal with this challenge. This methodology is based on constrained and unconstrained versions of a recently introduced 2-mode clustering model, the real-valued hierarchical classes model. The methodology is illustrated using empirical Person x Situation profile data on altruism.
Original languageEnglish
Pages (from-to)361-371
Number of pages11
JournalPsychological Methods
Volume16
Issue number3
DOIs
Publication statusPublished - Sep 2011

Keywords

  • profile data
  • two-mode clustering
  • nature of interaction
  • constrained and unconstrained RV-HICLAS
  • HIERARCHICAL CLASSES ANALYSIS
  • CLASSES ANALYSIS HICLAS
  • COMPONENT MODELS
  • PERSONALITY
  • DISPOSITIONS
  • COMPLEXITIES
  • IDENTITIES
  • SELECTION
  • DYNAMICS
  • SCIENCE

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