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Multiple Correspondence Analysis via Polynomial Transformations of Ordered Categorical Variables

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  • Rosaria Lombardo
  • Jacqueline Meulman

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Suggested Citation

  • Rosaria Lombardo & Jacqueline Meulman, 2010. "Multiple Correspondence Analysis via Polynomial Transformations of Ordered Categorical Variables," Journal of Classification, Springer;The Classification Society, vol. 27(2), pages 191-210, September.
  • Handle: RePEc:spr:jclass:v:27:y:2010:i:2:p:191-210
    DOI: 10.1007/s00357-010-9056-6
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    References listed on IDEAS

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    1. Lombardo, R. & Beh, E.J. & D'Ambra, L., 2007. "Non-symmetric correspondence analysis with ordinal variables using orthogonal polynomials," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 566-577, September.
    2. Michael Greenacre, 2008. "Correspondence analysis of raw data," Economics Working Papers 1112, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2009.
    3. Shizuhiko Nishisato, 1996. "Gleaning in the field of dual scaling," Psychometrika, Springer;The Psychometric Society, vol. 61(4), pages 559-599, December.
    4. Shizuhiko Nishisato & P. Arri, 1975. "Nonlinear programming approach to optimal scaling of partially ordered categories," Psychometrika, Springer;The Psychometric Society, vol. 40(4), pages 525-548, December.
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    Citations

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    Cited by:

    1. 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.
    2. Assuntina Cembalo & Rosaria Lombardo & Eric J. Beh & Gianpaolo Romano & Michele Ferrucci & Francesca M. Pisano, 2021. "Assessment of Climate Change in Italy by Variants of Ordered Correspondence Analysis," Stats, MDPI, vol. 4(1), pages 1-16, March.
    3. Rosaria Lombardo & Eric Beh & Antonello D'Ambra, 2011. "Studying the dependence between ordinal-nominal categorical variables via orthogonal polynomials," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(10), pages 2119-2132.
    4. Rosaria Lombardo & Eric Beh, 2010. "Simple and multiple correspondence analysis for ordinal-scale variables using orthogonal polynomials," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(12), pages 2101-2116.

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