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Conjoint use of variables clustering and PLS structural equations modelling

Author

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  • Valentina Stan

    (CEDRIC - Centre d'études et de recherche en informatique et communications - ENSIIE - Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise - CNAM - Conservatoire National des Arts et Métiers [CNAM])

  • Gilbert Saporta

    (CEDRIC - MSDMA - CEDRIC. Méthodes statistiques de data-mining et apprentissage - CEDRIC - Centre d'études et de recherche en informatique et communications - ENSIIE - Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise - CNAM - Conservatoire National des Arts et Métiers [CNAM])

Abstract

In PLS approach, it is frequently assumed that the blocks of variables satisfy the assumption of unidimensionality. In order to fulfill at best this hypothesis, we use clustering methods of variables. We illustrate the conjoint use of variables clustering and PLS structural equations modelling on data provided by PSA Company (Peugeot Citroën) on customers' satisfaction. The data are satisfaction scores on 32 manifest variables given by 2922 customers.

Suggested Citation

  • Valentina Stan & Gilbert Saporta, 2005. "Conjoint use of variables clustering and PLS structural equations modelling," Post-Print hal-01125056, HAL.
    • Handle: RePEc:hal:journl:hal-01125056
    Note: View the original document on HAL open archive server: https://hal.science/hal-01125056
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    File URL: https://hal.science/hal-01125056/document
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    Cited by:

    1. Jérome SARACCO & Marie CHAVENT & Vanessa KUENTZ, 2010. "Clustering of categorical variables around latent variables," Cahiers du GREThA (2007-2019) 2010-02, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).

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