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

  • Dades identificatives

    Identificador: imarina:9326008
    Autors:
    Lorenzo-Seva, UrbanoFerrando, Pere J
    Resum:
    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.
  • Altres:

    Autor segons l'article: Lorenzo-Seva, Urbano; Ferrando, Pere J
    Departament: Psicologia
    Autor/s de la URV: Ferrando Piera, Pere Joan / Lorenzo Seva, Urbano
    Paraules clau: Unrestricted factor analysis Uls Principal axis factoring Power analysis Minres Minimum rank factor analysis Goodness-of-fit indices Chi square test of fit statistic
    Resum: 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.
    Àrees temàtiques: Social sciences, mathematical methods Social sciences (miscellaneous) Social sciences (all) Psychology, mathematical Psychology (miscellaneous) Psychology (all) Psicología General social sciences General psychology Ciencias sociales
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    Adreça de correu electrònic de l'autor: urbano.lorenzo@urv.cat perejoan.ferrando@urv.cat
    Identificador de l'autor: 0000-0001-5369-3099 0000-0002-3133-5466
    Data d'alta del registre: 2024-10-12
    Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
    Enllaç font original: https://meth.psychopen.eu/index.php/meth/article/view/9839
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referència a l'article segons font original: Methodology-European Journal Of Research Methods For The Behavioral And Social Sciences. 19 (2): 96-115
    Referència 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 de l'article: 10.5964/meth.9839
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2023
    Tipus de publicació: Journal Publications
  • Paraules clau:

    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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