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Subset Correspondence Analysis

Author

Listed:
  • Michael Greenacre

    (Universitat Pompeu Fabra, Barcelona, Spain)

  • Rafael Pardo

    (Fundacion BBVA, Madrid, Spain)

Abstract

This study shows how correspondence analysis may be applied to a subset of response categories from a questionnaire survey (e.g., the subset of undecided responses or the subset of responses for a particular category across several questions). The idea is to maintain the original relative frequencies of the categories and not reexpress them relative to totals within the subset, as would normally be done in a regular correspondence analysis of the subset. Furthermore, the masses and chi-square distances assigned to the subset of categories are the same as those in the correspondence analysis of the whole data set, which leads to a decomposition of total variance into parts if the whole data set is subdivided into disjoint subsets. This variant of the method, called subset correspondence analysis, is illustrated on data from the International Social Survey Programme’s Family and Changing Gender Roles survey.

Suggested Citation

  • Michael Greenacre & Rafael Pardo, 2006. "Subset Correspondence Analysis," Sociological Methods & Research, , vol. 35(2), pages 193-218, November.
    • Handle: RePEc:sae:somere:v:35:y:2006:i:2:p:193-218
    DOI: 10.1177/0049124106290316
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    References listed on IDEAS

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    1. John Aitchison & Michael Greenacre, 2002. "Biplots of compositional data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 51(4), pages 375-392, October.
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    Citations

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    Cited by:

    1. Svetlana Zhuchkova & Aleksei Rotmistrov, 2022. "How to choose an approach to handling missing categorical data: (un)expected findings from a simulated statistical experiment," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(1), pages 1-22, February.
    2. Takane, Yoshio & Jung, Sunho, 2009. "Regularized nonsymmetric correspondence analysis," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3159-3170, June.
    3. Michael Greenacre & Patrick J. F Groenen & Trevor Hastie & Alfonso Iodice d’Enza & Angelos Markos & Elena Tuzhilina, 2023. "Principal component analysis," Economics Working Papers 1856, Department of Economics and Business, Universitat Pompeu Fabra.
    4. Menconi, M.E. & Tasso, S. & Santinelli, M. & Grohmann, D., 2020. "A card game to renew urban parks: Face-to-face and online approach for the inclusive involvement of local community," Evaluation and Program Planning, Elsevier, vol. 79(C).
    5. Ganiere, Pierre & Chern, Wen S. & Hahn, David E. & Chiang, Fu-Sung, 2004. "Consumer Attitudes towards Genetically Modified Foods in Emerging Markets: The Impact of Labeling in Taiwan," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 7(3), pages 1-20.
    6. Wenmei Yang & Adriano S. Koshiyama, 2019. "Assessing qualitative similarities between financial reporting frameworks using visualization and rules: COREP vs. pillar 3," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 26(1), pages 16-31, January.
    7. Blasius, Jörg & Eilers, Paul H.C. & Gower, John, 2009. "Better biplots," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3145-3158, June.
    8. Tor Korneliussen & Michael Greenacre, 2016. "Information sources used by European tourists: A cross-cultural study," Economics Working Papers 1527, Department of Economics and Business, Universitat Pompeu Fabra.
    9. Julie Josse & Marie Chavent & Benot Liquet & François Husson, 2012. "Handling Missing Values with Regularized Iterative Multiple Correspondence Analysis," Journal of Classification, Springer;The Classification Society, vol. 29(1), pages 91-116, April.
    10. Michael Greenacre & Paul Lewi, 2009. "Distributional Equivalence and Subcompositional Coherence in the Analysis of Compositional Data, Contingency Tables and Ratio-Scale Measurements," Journal of Classification, Springer;The Classification Society, vol. 26(1), pages 29-54, April.
    11. Josse, Julie & Husson, François, 2016. "missMDA: A Package for Handling Missing Values in Multivariate Data Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 70(i01).
    12. Ganiere, Pierre & Chern, Wen S. & Hahn, David E., 2004. "Who Are Proponents And Opponents Of Genetically Modified Foods In The United States?," Working Papers 28315, Ohio State University, Department of Agricultural, Environmental and Development Economics.

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