Abstract
The paper aims to introduce assessment and validation measures in Quantile Composite-based Path modeling. A quantile approach in the Partial Least Squares path modeling framework overcomes the classical exploration of average effects and highlights how and if the relationships among observed and unobserved variables change according to the explored quantile of interest. A final evaluation of the quality of the obtained results both from a descriptive (assessment) and inferential (validation) point of view is needed. The functioning of the proposed method is shown through a real data application in the area of the American Customer Satisfaction Index.
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Davino, C., Vinzi, V.E., Dolce, P. (2016). Assessment and Validation in Quantile Composite-Based Path Modeling. In: Abdi, H., Esposito Vinzi, V., Russolillo, G., Saporta, G., Trinchera, L. (eds) The Multiple Facets of Partial Least Squares and Related Methods. PLS 2014. Springer Proceedings in Mathematics & Statistics, vol 173. Springer, Cham. https://doi.org/10.1007/978-3-319-40643-5_13
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