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- Title
AN EXTENSION OF MULTIPLE CORRESPONDENCE ANALYSIS FOR IDENTIFYING HETEROGENEOUS SUBGROUPS OF RESPONDENTS.
- Authors
Hwang, Heungsun; Dillon, William R.; Takane, Yoshio
- Abstract
An extension of multiple correspondence analysis is proposed that takes into account cluster-level heterogeneity in respondents' preferences/choices. The method involves combining multiple correspondence analysis and k-means in a unified framework. The former is used for uncovering a low-dimensional space of multivariate categorical variables while the latter is used for identifying relatively homogeneous clusters of respondents. The proposed method offers an integrated graphical display that provides information on cluster-based structures inherent in multivariate categorical data as well as the interdependencies among the data. An empirical application is presented which demonstrates the usefulness of the proposed method and how it compares to several extant approaches.
- Subjects
MULTIVARIATE analysis; CLUSTER analysis (Statistics); CORRESPONDENCE analysis (Statistics); MATHEMATICAL statistics; RANDOM variables
- Publication
Psychometrika, 2006, Vol 71, Issue 1, p161
- ISSN
0033-3123
- Publication type
Article
- DOI
10.1007/S11336-004-1173-X