Between the observable and the latent: structural equations models and social research
Guardado en:
| Autores: | , |
|---|---|
| Formato: | artículo original |
| Estado: | Versión publicada |
| Fecha de Publicación: | 2024 |
| Descripción: | Introduction: The development of models and theories addressing sociocultural phenomena has been a challenge for empirical research in Social Sciences. Working with non-experimental and less controllable concepts has made it necessary to create more accurate methodologies for studying non-physical and abstract concepts, among which Structural Equation Models (SEM) are found. Objective: The aim is to analyze the potential of SEM to enhance the understanding of sociocultural phenomena within disciplines belonging to the Social Sciences. Method and technique: Initially, a bibliographic review was conducted regarding the origins of SEM. Subsequently, the structure and stages for their construction were detailed, followed by an analysis of the contributions these models offer to social research. Results: SEM allows for the understanding of complex relationships among variables inherent to social sciences and accounts for measurement errors in data. This enables the simultaneous analysis of multiple dependency relationships, unlike other approaches such as multiple regression or multivariate analysis. Conclusions: SEM is favorable for investigative activity and fosters the creation of new insights that contribute to the understanding and interpretation of various phenomena. This emphasizes the importance of constantly advancing knowledge related to the inherent complexities of social processes, to unveil the relationship between the observable and the latent. |
| País: | Portal de Revistas UCR |
| Institución: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| Lenguaje: | Español |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/58268 |
| Acceso en línea: | https://revistas.ucr.ac.cr/index.php/reflexiones/article/view/58268 |
| Palabra clave: | Idealizations Latent variables Causal relationships Scientific theories Statistical models Idealizaciones Variables latentes Relaciones causales Teorías científicas Modelos estadísticos |