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.
- profile data
- two-mode clustering
- nature of interaction
- constrained and unconstrained RV-HICLAS
- HIERARCHICAL CLASSES ANALYSIS
- CLASSES ANALYSIS HICLAS
- COMPONENT MODELS