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The objective of this paper is to describe and analyse with appropriate statistical models the links between work quality latent factors. Due to the complexity of the task, the analysis is carried out through a two-step approach:In the first step, we construct some multidimensional measures of the subjective quality of work, using nonlinear principal component analysis (NPCA) and Rasch analysis with the Rating Scale Model (NPCA-RSM);In the second step, we adopt a Structural Equation Model based on generalized maximum entropy (SEM-GME) to integrate the measures achieved with the previous step and to evaluate the relationships between the subjective work quality latent factors. Therefore, the novel aspects of this paper are the following: (i) The integration between the NPCA-RSM and SEM-GME, which allows reduction of the variables analysed and evaluation of the measurement errors; (ii) The formalization of a Job Satisfaction Model for the study of the relationships between the subjective work quality latent factors in the Italian social services sector. [ABSTRACT FROM AUTHOR]

This paper presents a review of the original method recently developed by the authors with the Generalized Maximum Entropy (GME) estimator for the simple linear Measurement Error Model (MEM) and the Structural Equation Model (SEM). In socio-economic research, these two models often concern subjective or psychological variables (composite indicators), and represent relations between latent variables. In this review, two applications to the statistical modelling of economic perception and job satisfaction are presented. [ABSTRACT FROM AUTHOR]