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Hwang, Heungsun; Dillon, William R. – Multivariate Behavioral Research, 2010
A 2-way clustering approach to multiple correspondence analysis is proposed to account for cluster-level heterogeneity of both respondents and variable categories in multivariate categorical data. Specifically, in the proposed method, multiple correspondence analysis is combined with k-means in a unified framework in which "k"-means is…
Descriptors: Data Analysis, Multivariate Analysis, Classification, Monte Carlo Methods
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van Buuren, Stef; de Leeuw, Jan – Multivariate Behavioral Research, 1992
Application of equality constraints on the categories of a variable is a simple and useful extension of multiple correspondence analysis. Equality is an easy way to incorporate prior knowledge. A procedure to deal with unequal category numbers and with subsets of variables is outlined and illustrated. (SLD)
Descriptors: Classification, Knowledge Level, Mathematical Models, Multivariate Analysis
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Millsap, Roger E.; Meredith, William – Multivariate Behavioral Research, 1991
Mathematical relationships between three-mode component analysis and stationary component analysis are explored. Theorems are presented giving constraints that must be satisfied for equivalency between component representations provided by the methods. In general, the two approaches give mathematically distinct representations. (SLD)
Descriptors: Classification, Equations (Mathematics), Longitudinal Studies, Mathematical Models
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Miller, Donald M.; And Others – Multivariate Behavioral Research, 1986
Two techniques compose a new methodology for studying certain classes of qualitative information: the F-sort task for data collection and latent partition analysis for data summarization. A detailed presentation is given of its application to a study of teacher's views of facilitating student learning in the classroom. (Author/LMO)
Descriptors: Classification, Concept Formation, Data Collection, Elementary Secondary Education