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ERIC Number: EJ720515
Record Type: Journal
Publication Date: 2005-Sep
Pages: 20
Abstractor: Author
Reference Count: 25
ISSN: ISSN-0033-3123
Hierarchical Classes Models for Three-Way Three-Mode Binary Data: Interrelations and Model Selection
Ceulemans, Eva; Van Mechelen, Iven
Psychometrika, v70 n3 p461-480 Sep 2005
Several hierarchical classes models can be considered for the modeling of three-way three-mode binary data, including the INDCLAS model (Leenen, Van Mechelen, De Boeck, and Rosenberg, 1999), the Tucker3-HICLAS model (Ceulemans,VanMechelen, and Leenen, 2003), the Tucker2-HICLAS model (Ceulemans and Van Mechelen, 2004), and the Tucker1-HICLAS model that is introduced in this paper. Two questions then may be raised: (1) how are these models interrelated, and (2) given a specific data set, which of these models should be selected, and in which rank? In the present paper, we deal with these questions by (1) showing that the distinct hierarchical classes models for three-way three-mode binary data can be organized into a partially ordered hierarchy, and (2) by presenting model selection strategies based on extensions of the well-known scree test and on the Akaike information criterion. The latter strategies are evaluated by means of an extensive simulation study and are illustrated with an application to interpersonal emotion data. Finally, the presented hierarchy and model selection strategies are related to corresponding work by Kiers (1991) for principal component models for three-way three-mode real-valued data.
Springer, 233 Spring Streeet, New York, NY 10013. Tel: 212-460-1539; Fax: 212-460-1594.
Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A