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.
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- 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