Abstract
The article is about the problem of the treatment of qualitative variables in the Structural Equation Models with attention to the case of Partial Least Squares Path Modeling. In literature there are some proposals based on the application of known statistical tecniques to quantify the qualitative variables. Starting from these works we propose an external quantification for only qualitative variables by the Alternating Least Squares, obtaining the optimal quantification (vectors of optimal scaling), a future objective to develop an algorithm that computes simultaneously the vectors of optimal scaling and the optimal regression coefficients, between the variables. We will present an application of our method to a real dataset.
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Lauro, C., Nappo, D., Grassia, M., Miele, R. (2011). Method of Quantification for Qualitative Variables and their Use in the Structural Equations Models. In: Fichet, B., Piccolo, D., Verde, R., Vichi, M. (eds) Classification and Multivariate Analysis for Complex Data Structures. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13312-1_34
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DOI: https://doi.org/10.1007/978-3-642-13312-1_34
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