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ERIC Number: EJ785467
Record Type: Journal
Publication Date: 2007-Dec
Pages: 14
Abstractor: Author
ISBN: N/A
ISSN: ISSN-0033-3123
EISSN: N/A
Hierarchical Classes Modeling of Rating Data
Van Mechelen, Iven; Lombardi, Luigi; Ceulemans, Eva
Psychometrika, v72 n4 p475-488 Dec 2007
Hierarchical classes (HICLAS) models constitute a distinct family of structural models for N-way N-mode data. All members of the family include N simultaneous and linked classifications of the elements of the N modes implied by the data; those classifications are organized in terms of hierarchical, if-then-type relations. Moreover, the models are accompanied by comprehensive, insightful graphical representations. Up to now, the hierarchical classes family has been limited to dichotomous or dichotomized data. In the present paper we propose a novel extension of the family to two-way two-mode rating data (HICLAS-R). The HICLAS-R model preserves the representation of simultaneous and linked classifications as well as of generalized if-then-type relations, and keeps being accompanied by a comprehensive graphical representation. It is shown to bear interesting relationships with classical real-valued two-way component analysis and with methods of optimal scaling.
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A