The aim of this paper is to propose an approach to quantify the qualitative variables, within Structural Equation Models (SEM), and in particular of PLS-PM. We propose a new algorithm, called Partial Alternating Least Squares Optimal Scaling- Path Modeling (PALSOS-PM), which through an iterative procedure, computes an optimal quantification, for qualitative variables, and structural parameters of the model chosen.
An alternating least square approach for the estimation of a SEM based on ordinal variables / Nappo, Daniela; Grassia, MARIA GABRIELLA. - In: STATISTICA APPLICATA. - ISSN 1125-1964. - STAMPA. - 20:3-4(2008), pp. 293-307.
An alternating least square approach for the estimation of a SEM based on ordinal variables
NAPPO, DANIELA;GRASSIA, MARIA GABRIELLA
2008
Abstract
The aim of this paper is to propose an approach to quantify the qualitative variables, within Structural Equation Models (SEM), and in particular of PLS-PM. We propose a new algorithm, called Partial Alternating Least Squares Optimal Scaling- Path Modeling (PALSOS-PM), which through an iterative procedure, computes an optimal quantification, for qualitative variables, and structural parameters of the model chosen.| File | Dimensione | Formato | |
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