The sampling design effect on partial least squares algorithm / El efecto de diseño de muestreo en el algoritmo de mÃnimos cuadrados parciales - Hugo Serrato González; Ignacio Méndez RamÃrez; Odette Lobato Calleros (RECI Revista Iberoamericana de las Ciencias Computacionales e Informática, 2016)
The objective of this article is to analyze the effect of the probability sampling’s selection on the estimated results in Structural Equation Modeling (SEM) using the Partial Least Squares (PLS) algorithm.The idea leading this work is to estimate the satisfaction level of government service users in a large and dispersed population, for which a sample design with an equal selection probability is not a feasible option. This study is based on the analysis of the sampling distributions of estimators under different sampling designs.It is shown that the probability of selection of the units behind the sampling design affect the results of the PLS algorithm, both the scores of latent variables and the impacts between them.To the author's knowledge, this issue has not been addressed before in the literature.