The Chapter deals with the Partial Least Squares (PLS) estimation algorithm and its use in the context of Structural Equation Models with Latent Variables (SEM-LV). After a short description of the general structure of SEM-LV models, the PLS algorithm is introduced; then, statistical and geometrical interpretations of PLS are given. A detailed application example based on the ABC Annual Customer Satisfaction Survey (ACSS) data concludes the Chapter.
Boari, G., Cantaluppi, G., PLS Models, in Salini, S., Kenett, R. S. (ed.), Modern Analysis of Customer Surveys: With Applications using R, John Wiley & Sons, Ltd:, Chichester. -- GBR 2012: 309- 332. 10.1002/9781119961154.ch16 [https://hdl.handle.net/10807/13159]
PLS Models
Boari, Giuseppe;Cantaluppi, Gabriele
2012
Abstract
The Chapter deals with the Partial Least Squares (PLS) estimation algorithm and its use in the context of Structural Equation Models with Latent Variables (SEM-LV). After a short description of the general structure of SEM-LV models, the PLS algorithm is introduced; then, statistical and geometrical interpretations of PLS are given. A detailed application example based on the ABC Annual Customer Satisfaction Survey (ACSS) data concludes the Chapter.
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