En el presente trabajo se expone una aproximación conceptual y práctica a los Modelos de Ecuaciones Estructurales o Structural Equation Modeling (SEM). Los SEM están considerados entre las herramientas más potentes para el estudio de relaciones causales en datos no experimentales. Son una combinación del análisis factorial y la regresión múltiple y están compuestos por dos componentes: el modelo de medida y el modelo estructural. El modelo de medida describe la relación existente entre una serie de variables observables; mientras que en el modelo estructural se especifican las relaciones hipotetizadas entre las variables, es decir, se describen las relaciones entre las variables latentes mediante el uso de flechas. Llevar a cabo un SEM involucra cinco etapas: 1) Especificación del Modelo; 2) Identificación del Modelo; 3) Estimación del Modelo; 4) Evaluación del Modelo y 5) ...

This methodological article explains a conceptual and practical approach to Structural Equation Models or Structural Equation Modeling (SEM). SEMs are considered among the most powerful tools for the study of causal relationships in non-experimental data. They are a combination of factor analysis and multiple regression and are composed of two components: the measurement model and the structural model. The measurement model describes the relationship between a series of observable variables; while in the structural model the relationships between variables are hypothesized; i.e., the relationships between latent variables are described with the use of arrows. Performing a SEM involves five stages: (1) A specification of the Model; (2) Identification of the Model; (3) Estimation of the Model; (4) Evaluation of the Model and (5) Re-specification of the Model. This article provides a series...

This methodological article explains a conceptual and practical approach to Structural Equation Models or Structural Equation Modeling (SEM). SEMs are considered among the most powerful tools for the study of causal relationships in non-experimental data. They are a combination of factor analysis and multiple regression and are composed of two components: the measurement model and the structural model. The measurement model describes the relationship between a series of observable variables; while in the structural model the relationships between variables are hypothesized; i.e., the relationships between latent variables are described with the use of arrows. Performing a SEM involves five stages: (1) A specification of the Model; (2) Identification of the Model; (3) Estimation of the Model; (4) Evaluation of the Model and (5) Re-specification of the Model. This article provides a series...

The pursuit of happiness is one of the most coveted goals of human beings. There are increasingly more psychology studies seeking to find which factors are involved in happiness. There are two main approaches to this study: the hedonic and the eudaemonic paradigms. The hedonic paradigm proposes that well-being depends primarily on living a life with pleasant experiences, while the eudaemonic paradigm refers that well-being is not only achieved through pleasure, but mainly through upgrading the human potential. In the present study we worked with a sample consisting of 340 citizens of Cordoba (Argentina) to investigate which conceptions they have about happiness by the technique of Natural Semantic Networks (NSN). Two hypotheses were proposed in this regard: 1) participants will conceive happiness both in hedonic and eudaemonic terms, and 2) those participants with higher levels of happin...