The aim of the chapter is to provide step-by-step instructions to imple-ment, estimate, and interpret a Quantile Composite-based Path Model, exploiting the qcpm package (https://rdrr.io/cran/qcpm/), freely available for the R software. The chapter encompasses both methodological aspects of this recent quantile approach to Partial Least Squares Path Modeling, and real data applications, so as to offer a com-prehensive guide to the readers interested in the use of the method on their own data. All steps of a quantitative analysis, i.e., data loading, pre-processing, coefficient esti-mation and model validation are described showing the options and functionalities of the package along with the corresponding methodology.
Quantile Composite-Based Path Modeling with R: A Hands-on Guide / Davino, Cristina; Dolce, Pasquale; Lamberti, Giuseppe; Vistocco, Domenico. - (2023). [10.1007/978-3-031-37772-3]
Quantile Composite-Based Path Modeling with R: A Hands-on Guide
Cristina Davino
;Pasquale Dolce;Domenico Vistocco
2023
Abstract
The aim of the chapter is to provide step-by-step instructions to imple-ment, estimate, and interpret a Quantile Composite-based Path Model, exploiting the qcpm package (https://rdrr.io/cran/qcpm/), freely available for the R software. The chapter encompasses both methodological aspects of this recent quantile approach to Partial Least Squares Path Modeling, and real data applications, so as to offer a com-prehensive guide to the readers interested in the use of the method on their own data. All steps of a quantitative analysis, i.e., data loading, pre-processing, coefficient esti-mation and model validation are described showing the options and functionalities of the package along with the corresponding methodology.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
