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A Simple Two-Step Procedure for Fitting Fully Unrestricted Exploratory Factor Analytic Solutions with Correlated Residuals

  • Datos identificativos

    Identificador: imarina:9333720
    Autores:
    Ferrando, Pere JHernandez-Dorado, AnaLorenzo-Seva, Urbano
    Resumen:
    A frequent criticism of exploratory factor analysis (EFA) is that it does not allow correlated residuals to be modelled, while they can be routinely specified in the confirmatory (CFA) model. In this article, we propose an EFA approach in which both the common factor solution and the residual matrix are unrestricted (i.e., the correlated residuals need not be specified a priori). The estimation procedures are two-stage and based on the unweighted least squares principle. Procedures for judging the solution appropriateness (including goodness of fit) are also proposed. The simulation studies and illustrative example suggest that the approach works quite well Although the proposal is based on existing results, most of the developments can be considered to be new contributions, and are expected to be particularly useful in the earlier stages of item calibration. The whole procedure has been implemented in both R language and a well-known non-commercial EFA program.
  • Otros:

    Autor según el artículo: Ferrando, Pere J; Hernandez-Dorado, Ana; Lorenzo-Seva, Urbano
    Departamento: Psicologia
    Autor/es de la URV: Ferrando Piera, Pere Joan / Lorenzo Seva, Urbano
    Palabras clave: Number Monte-carlo Local dependence Linear and nonlinear factor analysis Item analysis Goodness-of-fit Exploratory factor analysis Correlated residuals
    Resumen: A frequent criticism of exploratory factor analysis (EFA) is that it does not allow correlated residuals to be modelled, while they can be routinely specified in the confirmatory (CFA) model. In this article, we propose an EFA approach in which both the common factor solution and the residual matrix are unrestricted (i.e., the correlated residuals need not be specified a priori). The estimation procedures are two-stage and based on the unweighted least squares principle. Procedures for judging the solution appropriateness (including goodness of fit) are also proposed. The simulation studies and illustrative example suggest that the approach works quite well Although the proposal is based on existing results, most of the developments can be considered to be new contributions, and are expected to be particularly useful in the earlier stages of item calibration. The whole procedure has been implemented in both R language and a well-known non-commercial EFA program.
    Áreas temáticas: Sociology and political science Sociologia i política Social sciences, mathematical methods Psychology Psicología Modeling and simulation Mathematics, interdisciplinary applications Matemática / probabilidade e estatística General o multidisciplinar General economics,econometrics and finance General decision sciences Economics, econometrics and finance (miscellaneous) Economics, econometrics and finance (all) Economia Decision sciences (miscellaneous) Decision sciences (all) Ciencias sociales
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: urbano.lorenzo@urv.cat perejoan.ferrando@urv.cat
    Identificador del autor: 0000-0001-5369-3099 0000-0002-3133-5466
    Fecha de alta del registro: 2024-10-12
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://www.tandfonline.com/doi/full/10.1080/10705511.2023.2267181
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Structural Equation Modeling-A Multidisciplinary Journal. 31 (3): 420-428
    Referencia de l'ítem segons les normes APA: Ferrando, Pere J; Hernandez-Dorado, Ana; Lorenzo-Seva, Urbano (2024). A Simple Two-Step Procedure for Fitting Fully Unrestricted Exploratory Factor Analytic Solutions with Correlated Residuals. Structural Equation Modeling-A Multidisciplinary Journal, 31(3), 420-428. DOI: 10.1080/10705511.2023.2267181
    DOI del artículo: 10.1080/10705511.2023.2267181
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2024
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Decision Sciences (Miscellaneous),Economics, Econometrics and Finance (Miscellaneous),Mathematics, Interdisciplinary Applications,Modeling and Simulation,Social Sciences, Mathematical Methods,Sociology and Political Science
    Number
    Monte-carlo
    Local dependence
    Linear and nonlinear factor analysis
    Item analysis
    Goodness-of-fit
    Exploratory factor analysis
    Correlated residuals
    Sociology and political science
    Sociologia i política
    Social sciences, mathematical methods
    Psychology
    Psicología
    Modeling and simulation
    Mathematics, interdisciplinary applications
    Matemática / probabilidade e estatística
    General o multidisciplinar
    General economics,econometrics and finance
    General decision sciences
    Economics, econometrics and finance (miscellaneous)
    Economics, econometrics and finance (all)
    Economia
    Decision sciences (miscellaneous)
    Decision sciences (all)
    Ciencias sociales
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