Structural equations models and their application to risk perception
Quantitative research requires the use of statistical methods. Generally, a researcher starts from a theoretical model and gathers the necessary information to validate it. However, the descriptive or exploratory characteristics of most statistical models which evaluate interaction among a...
| Autores principales: | , |
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| Formato: | Artículo publishedVersion |
| Lenguaje: | Español |
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CIMBAGE - IADCOM - Facultad de Ciencias Económicas - Universidad de Buenos Aires
2018
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| Materias: | |
| Acceso en línea: | https://ojs.economicas.uba.ar/CIMBAGE/article/view/1183 https://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=cimbage&d=1183_oai |
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I28-R145-1183_oai |
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dspace |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-145 |
| collection |
Repositorio Digital de la Universidad de Buenos Aires (UBA) |
| language |
Español |
| orig_language_str_mv |
spa |
| topic |
Modelos de Ecuaciones Estructurales Percepción del Riesgo Factores Latentes Structural Equation Models, atent Factors, Risk Perception |
| spellingShingle |
Modelos de Ecuaciones Estructurales Percepción del Riesgo Factores Latentes Structural Equation Models, atent Factors, Risk Perception Lepera, Andrea Muiños, Roberto Structural equations models and their application to risk perception |
| topic_facet |
Modelos de Ecuaciones Estructurales Percepción del Riesgo Factores Latentes Structural Equation Models, atent Factors, Risk Perception |
| description |
Quantitative research requires the use of statistical methods. Generally, a researcher starts from a theoretical model and gathers the necessary information to validate it. However, the descriptive or exploratory characteristics of most statistical models which evaluate interaction among a number of variables simultaneously render this task more difficult. Structural equation models (SEM), given their
confirmatory nature, allow for the use of empirical data to evaluate the validity of the theoretical model
considered.
SEMs express the relationship among a few variables, which can either be directly observable or not observable at all. Many of the most widely used statistical models may be considered particular cases of SEM, including linear regression, canonical correlation analysis, path analysis, and confirmatory factor analysis. Nonetheless, some of SEM characteristics clearly distinguish it from both the univariate and the multivariate models. Multivariate techniques only examine the relationships between two or more observable variables,
providing no possibility to consider hypothetical, non - observable variables. Most of these techniques are exploratory, i.e., they look for general patterns defined by the observed data itself. The SEM is of a confirmatory nature, i.e., the design of relationships among variables must be previously made explicit
on the basis of theoretical expectations. This distinctive feature makes this method especially adequate for testing theoretical models through the use of empirical data.
This paper presents the main theoretical - conceptual characteristics of Structural Equation Models, along with their application to a psychological research. |
| format |
Artículo publishedVersion |
| author |
Lepera, Andrea Muiños, Roberto |
| author_facet |
Lepera, Andrea Muiños, Roberto |
| author_sort |
Lepera, Andrea |
| title |
Structural equations models and their application to risk perception |
| title_short |
Structural equations models and their application to risk perception |
| title_full |
Structural equations models and their application to risk perception |
| title_fullStr |
Structural equations models and their application to risk perception |
| title_full_unstemmed |
Structural equations models and their application to risk perception |
| title_sort |
structural equations models and their application to risk perception |
| publisher |
CIMBAGE - IADCOM - Facultad de Ciencias Económicas - Universidad de Buenos Aires |
| publishDate |
2018 |
| url |
https://ojs.economicas.uba.ar/CIMBAGE/article/view/1183 https://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=cimbage&d=1183_oai |
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AT leperaandrea structuralequationsmodelsandtheirapplicationtoriskperception AT muinosroberto structuralequationsmodelsandtheirapplicationtoriskperception AT leperaandrea losmodelosdeecuacionesestructuralesysuaplicacionalaevaluaciondelriesgopercibido AT muinosroberto losmodelosdeecuacionesestructuralesysuaplicacionalaevaluaciondelriesgopercibido |
| _version_ |
1825551029865807872 |
| spelling |
I28-R145-1183_oai2025-02-11 Lepera, Andrea Muiños, Roberto 2018-09-19 Quantitative research requires the use of statistical methods. Generally, a researcher starts from a theoretical model and gathers the necessary information to validate it. However, the descriptive or exploratory characteristics of most statistical models which evaluate interaction among a number of variables simultaneously render this task more difficult. Structural equation models (SEM), given their confirmatory nature, allow for the use of empirical data to evaluate the validity of the theoretical model considered. SEMs express the relationship among a few variables, which can either be directly observable or not observable at all. Many of the most widely used statistical models may be considered particular cases of SEM, including linear regression, canonical correlation analysis, path analysis, and confirmatory factor analysis. Nonetheless, some of SEM characteristics clearly distinguish it from both the univariate and the multivariate models. Multivariate techniques only examine the relationships between two or more observable variables, providing no possibility to consider hypothetical, non - observable variables. Most of these techniques are exploratory, i.e., they look for general patterns defined by the observed data itself. The SEM is of a confirmatory nature, i.e., the design of relationships among variables must be previously made explicit on the basis of theoretical expectations. This distinctive feature makes this method especially adequate for testing theoretical models through the use of empirical data. This paper presents the main theoretical - conceptual characteristics of Structural Equation Models, along with their application to a psychological research. La investigación cuantitativa requiere de la utilización de métodos estadísticos. El investigador, en general, parte de un modelo teórico y recoge la información necesaria para validarlo. Sin embargo, las características descriptivas o exploratorias de la mayoría de los modelos estadísticos que evalúan la interacción entre varias variables simultáneamente, dificultan esta tarea. Los modelos de ecuaciones estructurales (SEM, según sus siglas en inglés), por su carácter confirmatorio, permiten utilizar datos empíricos para evaluar la validez del modelo teórico considerado. Los modelos SEM expresan la relación entre distintas variables, las cuales pueden ser directamente observables o no observables. Muchos de los modelos estadísticos más utilizados pueden considerarse casos particulares de SEM, incluyendo regresión lineal, análisis de correlación canónica, Path análisis, y el análisis factorial confirmatorio. Sin embargo, algunas características del SEM lo distinguen claramente tanto de los modelos univariados como de los multivariados. Las técnicas multivariadas se limitan a examinar las relaciones entre dos o más variables observables, sin posibilidad de considerar variables hipotéticas, no observables directamente. La mayoría de estas técnicas son de carácter exploratorio: buscan patrones generales definidos por los propios datos observados. El SEM es de carácter confirmatorio: el diseño de relaciones entre las variables debe ser explicitado a priori sobre la base de expectativas teóricas. Esta característica distintiva del método lo hace especialmente adecuado para testear modelos teóricos mediante la utilización de datos empíricos. En este trabajo se presentan las principales características teórico- conceptuales de los Modelos de Ecuaciones Estructurales, conjuntamente con una aplicación a una investigación psicológica. application/pdf https://ojs.economicas.uba.ar/CIMBAGE/article/view/1183 spa CIMBAGE - IADCOM - Facultad de Ciencias Económicas - Universidad de Buenos Aires https://ojs.economicas.uba.ar/CIMBAGE/article/view/1183/1792 Cuadernos del CIMBAGE; Vol. 1 No. 20 (2018): Cuadernos del CIMBAGE; 85-105 Cuadernos del CIMBAGE; Vol. 1 Núm. 20 (2018): Cuadernos del CIMBAGE; 85-105 1669-1830 1666-5112 Modelos de Ecuaciones Estructurales Percepción del Riesgo Factores Latentes Structural Equation Models, atent Factors, Risk Perception Structural equations models and their application to risk perception Los modelos de ecuaciones estructurales y su aplicación a la evaluación del riesgo percibido info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion https://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=cimbage&d=1183_oai |