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Extending dual multiple factor analysis to categorical tables

Author

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  • Elena Abascal
  • Vidal D�az de Rada
  • Ignacio Garc�a Lautre
  • M. Isabel Landaluce

Abstract

This paper describes a proposal for the extension of the dual multiple factor analysis (DMFA) method developed by Lê and Pagès 15 to the analysis of categorical tables in which the same set of variables is measured on different sets of individuals. The extension of DMFA is based on the transformation of categorical variables into properly weighted indicator variables, in a way analogous to that used in the multiple factor analysis of categorical variables. The DMFA of categorical variables enables visual comparison of the association structures between categories over the sample as a whole and in the various subsamples (sets of individuals). For each category, DMFA allows us to obtain its global (considering all the individuals) and partial (considering each set of individuals) coordinates in a factor space. This visual analysis allows us to compare the set of individuals to identify their similarities and differences. The suitability of the technique is illustrated through two applications: one using simulated data for two groups of individuals with very different association structures and the other using real data from a voting intention survey in which some respondents were interviewed by telephone and others face to face. The results indicate that the two data collection methods, while similar, are not entirely equivalent.

Suggested Citation

  • Elena Abascal & Vidal D�az de Rada & Ignacio Garc�a Lautre & M. Isabel Landaluce, 2013. "Extending dual multiple factor analysis to categorical tables," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(2), pages 415-428, February.
    • Handle: RePEc:taf:japsta:v:40:y:2013:i:2:p:415-428
    DOI: 10.1080/02664763.2012.745836
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    Cited by:

    1. Jaime DE PABLO-VALENCIANO & Valentin TASSILE & Miguel Ángel GIACINTI-BATTISTUZZI & Juan MILÁN-GARCÍA, 2020. "Analysis Of Trade: Import Of Pears In India (2015-2018)," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 20(2), pages 97-108.
    2. Zhi-Sheng Ye & Jian-Guo Li & Mengru Zhang, 2014. "Application of ridge regression and factor analysis in design and production of alloy wheels," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(7), pages 1436-1452, July.

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