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An Extension of Multiple Correspondence Analysis for Identifying Heterogeneous Subgroups of Respondents

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  • Heungsun Hwang
  • Hec Montréal
  • William Dillon
  • Yoshio Takane

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  • Heungsun Hwang & Hec Montréal & William Dillon & Yoshio Takane, 2006. "An Extension of Multiple Correspondence Analysis for Identifying Heterogeneous Subgroups of Respondents," Psychometrika, Springer;The Psychometric Society, vol. 71(1), pages 161-171, March.
    • Handle: RePEc:spr:psycho:v:71:y:2006:i:1:p:161-171
    DOI: 10.1007/s11336-004-1173-x
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    References listed on IDEAS

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    1. J. O. Ramsay, 1998. "Estimating smooth monotone functions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(2), pages 365-375.
    2. Wei‐Chien Chang, 1983. "On Using Principal Components before Separating a Mixture of Two Multivariate Normal Distributions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 32(3), pages 267-275, November.
    3. Heungsun Hwang & Yoshio Takane, 2002. "Generalized constrained multiple correspondence analysis," Psychometrika, Springer;The Psychometric Society, vol. 67(2), pages 211-224, June.
    4. Vichi, Maurizio & Kiers, Henk A. L., 2001. "Factorial k-means analysis for two-way data," Computational Statistics & Data Analysis, Elsevier, vol. 37(1), pages 49-64, July.
    5. Michael Greenacre, 2008. "Correspondence analysis of raw data," Economics Working Papers 1112, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2009.
    6. Wagner A. Kamakura & Byung-Do Kim & Jonathan Lee, 1996. "Modeling Preference and Structural Heterogeneity in Consumer Choice," Marketing Science, INFORMS, vol. 15(2), pages 152-172.
    7. Paul Green & Jonathan Kim & Frank Carmone, 1990. "A preliminary study of optimal variable weighting in k-means clustering," Journal of Classification, Springer;The Classification Society, vol. 7(2), pages 271-285, September.
    8. J. Kruskal, 1964. "Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis," Psychometrika, Springer;The Psychometric Society, vol. 29(1), pages 1-27, March.
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    Cited by:

    1. Cristina Tortora & Mireille Gettler Summa & Marina Marino & Francesco Palumbo, 2016. "Factor probabilistic distance clustering (FPDC): a new clustering method," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 10(4), pages 441-464, December.
    2. Dawn Iacobucci & Doug Grisaffe, 2018. "Perceptual maps via enhanced correspondence analysis: representing confidence regions to clarify brand positions," Journal of Marketing Analytics, Palgrave Macmillan, vol. 6(3), pages 72-83, September.
    3. M. Velden & A. Iodice D’Enza & F. Palumbo, 2017. "Cluster Correspondence Analysis," Psychometrika, Springer;The Psychometric Society, vol. 82(1), pages 158-185, March.
    4. Monia Ranalli & Roberto Rocci, 2017. "A Model-Based Approach to Simultaneous Clustering and Dimensional Reduction of Ordinal Data," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 1007-1034, December.
    5. Rosaria Lombardo & Ida Camminatiello & Eric J. Beh, 2019. "Assessing Satisfaction with Public Transport Service by Ordered Multiple Correspondence Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(1), pages 355-369, May.
    6. Masaki Mitsuhiro & Hiroshi Yadohisa, 2015. "Reduced $$k$$ k -means clustering with MCA in a low-dimensional space," Computational Statistics, Springer, vol. 30(2), pages 463-475, June.
    7. Alfonso Iodice D’Enza & Francesco Palumbo, 2013. "Iterative factor clustering of binary data," Computational Statistics, Springer, vol. 28(2), pages 789-807, April.
    8. Kensuke Tanioka & Hiroshi Yadohisa, 2019. "Simultaneous Method of Orthogonal Non-metric Non-negative Matrix Factorization and Constrained Non-hierarchical Clustering," Journal of Classification, Springer;The Classification Society, vol. 36(1), pages 73-93, April.
    9. John Rodwell & Thomas Hendry & Dianne Johnson, 2022. "A Parsimonious Taxonomy of The Newly Retired: Spousal and Disability Combinations Shape Part or Complete Retirement," IJERPH, MDPI, vol. 19(20), pages 1-13, October.

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