A presentation of the Partial Least Squares approach to Structural Equation Modeling (or PLS Path Modeling) is given together with a discussion of its extensions. This approach is compared with the estimation of Structural Equation Modeling by means of maximum likelihood (SEM-ML). Notwithstanding, this approach still shows some weaknesses. In this respect, some new improvements are proposed. Furthermore, PLS path modeling can be used for analyzing multiple tables so as to be related to more classical data analysis methods used in this ÿeld. Finally, a complete treatment of a real example is shown through the available software.
PLS Path Modeling / Tenenhaus, M.; ESPOSITO VINZI, V.; Chatlein, Y.; Lauro, Natale. - In: COMPUTATIONAL STATISTICS & DATA ANALYSIS. - ISSN 0167-9473. - STAMPA. - 48:(2005), pp. 159-205.
PLS Path Modeling
LAURO, NATALE
2005
Abstract
A presentation of the Partial Least Squares approach to Structural Equation Modeling (or PLS Path Modeling) is given together with a discussion of its extensions. This approach is compared with the estimation of Structural Equation Modeling by means of maximum likelihood (SEM-ML). Notwithstanding, this approach still shows some weaknesses. In this respect, some new improvements are proposed. Furthermore, PLS path modeling can be used for analyzing multiple tables so as to be related to more classical data analysis methods used in this ÿeld. Finally, a complete treatment of a real example is shown through the available software.File | Dimensione | Formato | |
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