
doi: 10.1007/bf02295642
This paper presents a new hierarchical classes model, called Tucker2-HICLAS, for binary three-way three-mode data. As any three-way hierarchical classes model, the Tucker2-HICLAS model includes a representation of the association relation among the three modes and a hierarchical classification of the elements of each mode. A distinctive feature of the Tucker2-HICLAS model, being closely related to the Tucker3-HICLAS model (Ceulemans, Van Mechelen & Leenen, 2003), is that one of the three modes is minimally reduced and, hence, that the differences among the association patterns of the elements of this mode are maximally retained in the model. Moreover, as compared to Tucker3-HICLAS, Tucker2-HICLAS implies three rather than four different types of parameters and as such is simpler to interpret. Two types of Tucker2-HICLAS models are distinguished: a disjunctive and a conjunctive type. An algorithm for fitting the Tucker2-HICLAS model is described and evaluated in a simulation study. The model is illustrated with longitudinal data on interpersonal emotions.
Classification and discrimination; cluster analysis (statistical aspects), Other matrix algorithms, multiway data analysis, hierarchical classes, three-way three-mode data, binary data, Multilinear algebra, tensor calculus, Vector and tensor algebra, theory of invariants, Applications of statistics to psychology, clustering
Classification and discrimination; cluster analysis (statistical aspects), Other matrix algorithms, multiway data analysis, hierarchical classes, three-way three-mode data, binary data, Multilinear algebra, tensor calculus, Vector and tensor algebra, theory of invariants, Applications of statistics to psychology, clustering
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