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A Simulation-Based Scaled Test Statistic for Assessing Model-Data Fit in Least-Squares Unrestricted Factor-Analysis Solutions

  • Datos identificativos

    Identificador: imarina:9326008
    Autores:
    Lorenzo-Seva, UrbanoFerrando, Pere J
    Resumen:
    A shortcoming of least-squares unrestricted factor analysis (UFA) procedures, which are widely used in psychometric applications is that a test statistic for assessing model-data fit cannot be easily derived from the minimum fit function value. This paper proposes a chi-square type goodness-of-fit test statistic intended for the principal-axis, MINRES, and minimum-rank UFA procedures. The statistic is empirically obtained via intensive simulation based on a two-stage approach. First, a distribution of minimum fit function values is obtained from a scenario in which the null hypothesis of perfect model-data fit holds. Second, the obtained statistic is non-linearly transformed so that it has its first four moments equal to those of the theoretical reference chi-square distribution with the appropriate degrees of freedom. Extensions of the basic statistic are next proposed that include comparative and relative indexes based on it. Tests of close-fit and power assessment derived from the basic statistic are also proposed.
  • Otros:

    Autor según el artículo: Lorenzo-Seva, Urbano; Ferrando, Pere J
    Departamento: Psicologia
    Autor/es de la URV: Ferrando Piera, Pere Joan / Lorenzo Seva, Urbano
    Palabras clave: Unrestricted factor analysis Uls Principal axis factoring Power analysis Minres Minimum rank factor analysis Goodness-of-fit indices Chi square test of fit statistic
    Resumen: A shortcoming of least-squares unrestricted factor analysis (UFA) procedures, which are widely used in psychometric applications is that a test statistic for assessing model-data fit cannot be easily derived from the minimum fit function value. This paper proposes a chi-square type goodness-of-fit test statistic intended for the principal-axis, MINRES, and minimum-rank UFA procedures. The statistic is empirically obtained via intensive simulation based on a two-stage approach. First, a distribution of minimum fit function values is obtained from a scenario in which the null hypothesis of perfect model-data fit holds. Second, the obtained statistic is non-linearly transformed so that it has its first four moments equal to those of the theoretical reference chi-square distribution with the appropriate degrees of freedom. Extensions of the basic statistic are next proposed that include comparative and relative indexes based on it. Tests of close-fit and power assessment derived from the basic statistic are also proposed.
    Áreas temáticas: Social sciences, mathematical methods Social sciences (miscellaneous) Social sciences (all) Psychology, mathematical Psychology (miscellaneous) Psychology (all) Psicología General social sciences General psychology 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://meth.psychopen.eu/index.php/meth/article/view/9839
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Methodology-European Journal Of Research Methods For The Behavioral And Social Sciences. 19 (2): 96-115
    Referencia de l'ítem segons les normes APA: Lorenzo-Seva, Urbano; Ferrando, Pere J (2023). A Simulation-Based Scaled Test Statistic for Assessing Model-Data Fit in Least-Squares Unrestricted Factor-Analysis Solutions. Methodology-European Journal Of Research Methods For The Behavioral And Social Sciences, 19(2), 96-115. DOI: 10.5964/meth.9839
    DOI del artículo: 10.5964/meth.9839
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2023
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Psychology (Miscellaneous),Psychology, Mathematical,Social Sciences (Miscellaneous),Social Sciences, Mathematical Methods
    Unrestricted factor analysis
    Uls
    Principal axis factoring
    Power analysis
    Minres
    Minimum rank factor analysis
    Goodness-of-fit indices
    Chi square test of fit statistic
    Social sciences, mathematical methods
    Social sciences (miscellaneous)
    Social sciences (all)
    Psychology, mathematical
    Psychology (miscellaneous)
    Psychology (all)
    Psicología
    General social sciences
    General psychology
    Ciencias sociales
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