Análisis factorial exploratorio mediante el uso de las medidas de adecuación muestral kmo y esfericidad de bartlett para determinar factores principales

Abstract

The objective of this research is to demonstrate the importance of the statistical technique of Exploratory Factor Analysis (EFA). The methodology used was through the KMO test (Kaiser, Meyer and Olkin), applicability of the factor analysis of the variables studied, by means of the Bartlett test of sphericity, as well as the percentage of explained variance, polychoric matrices and components of main factors. The database shows 27 variables, in order to achieve a better model, only 18. The results achieved, where the measurement scale is on the Likert scale, determined that the best model, based on the highest accumulated variance, was that of four factors with a percentage of 51%.