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 modeling on data provided by PSA Company (Peugeot Citroën) on customers’ satisfaction. The data are satisfaction scores on 32 manifest variables given by 2,922 customers.
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Stan, V., Saporta, G. (2010). Conjoint Use of Variables Clustering and PLS Structural Equations Modeling. In: Esposito Vinzi, V., Chin, W., Henseler, J., Wang, H. (eds) Handbook of Partial Least Squares. Springer Handbooks of Computational Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32827-8_11
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DOI: https://doi.org/10.1007/978-3-540-32827-8_11
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