Hierarchical classes models for three-way three-mode binary data: interrelations and model selection

By Eva Ceulemans, I. Van Mechelen. 2005

46 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Mathematics, Signal Processing

View Paper: https://www.semanticscholar.org/paper/282a0df124bde7c84e67737bca6a0e6ab1d06902

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Citations in the corpus

• Measuring identity multiplicity and intersectionality: Hierarchical Classes Analysis (HICLAS) of sexual, racial, and gender identities (2008, background): “More recently, hierarchical classes models have been developed that can accommodate ordinal data (Leenen, Van Mechelen, & De Boeck, 2001 ), as well as three-way, three-mode data arrays (Ceulemans & Van Mechelen, 2005 ).”
• The Hull Method for Selecting the Number of Common Factors (2011, unknown): “, Comrey, 1978; Fava & Velicer, 1992; Levonian & Comrey, 1966; Wood, Tataryn, & Gorsuch, 1996). Underfactoring, which is an underestimation of the number of factors, makes the factor loading patterns artificially complex and, therefore, the factors difficult to interpret (see Comrey, 1978). On the o”