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Detecting Correlated Residuals in Exploratory Factor Analysis: New Proposals and a Comparison of Procedures

  • Dades identificatives

    Identificador: imarina:9243511
    Autors:
    Ferrando, Pere JHernandez-Dorado, AnaLorenzo-Seva, Urbano
    Resum:
    In the classical exploratory factor analysis (EFA) model, residuals are constrained to be uncorrelated. However, since the 1960s, extensions of the classical model that allow correlated residuals to be modeled exist. Furthermore, in many EFA applications (especially those intended for item analysis) it is highly relevant to decide whether an extended solution is more appropriate than the simpler classical solution. This decision, in turn, requires effective and powerful methods for detecting correlated residuals (doublets) when they are really present to be available. This paper discusses two existing detection approaches in the EFA context, and proposes a third, new procedure. Reference values, based on the concept of parallel analysis, are proposed for deciding the relevance of the flagged doublets in all the considered procedures. The functioning of the three procedures is assessed by using simulation, and illustrated with an illustrative example. The proposal, finally, has been implemented in a well-known noncommercial EFA program, and an implementation in R is being developed.
  • Altres:

    Autor segons l'article: Ferrando, Pere J; Hernandez-Dorado, Ana; Lorenzo-Seva, Urbano
    Departament: Psicologia
    Autor/s de la URV: Ferrando Piera, Pere Joan / Hernández Dorado, Ana / Lorenzo Seva, Urbano
    Paraules clau: Parallel analysis Index Image theory Exploratory factor analysis Expected parameter change Doublets Correlated residuals
    Resum: In the classical exploratory factor analysis (EFA) model, residuals are constrained to be uncorrelated. However, since the 1960s, extensions of the classical model that allow correlated residuals to be modeled exist. Furthermore, in many EFA applications (especially those intended for item analysis) it is highly relevant to decide whether an extended solution is more appropriate than the simpler classical solution. This decision, in turn, requires effective and powerful methods for detecting correlated residuals (doublets) when they are really present to be available. This paper discusses two existing detection approaches in the EFA context, and proposes a third, new procedure. Reference values, based on the concept of parallel analysis, are proposed for deciding the relevance of the flagged doublets in all the considered procedures. The functioning of the three procedures is assessed by using simulation, and illustrated with an illustrative example. The proposal, finally, has been implemented in a well-known noncommercial EFA program, and an implementation in R is being developed.
    Àrees temàtiques: 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
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    Adreça de correu electrònic de l'autor: ana.hernandez@urv.cat 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://www.tandfonline.com/doi/full/10.1080/10705511.2021.2004543
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referència a l'article segons font original: Structural Equation Modeling-A Multidisciplinary Journal. 29 (4): 630-638
    Referència de l'ítem segons les normes APA: Ferrando, Pere J; Hernandez-Dorado, Ana; Lorenzo-Seva, Urbano (2022). Detecting Correlated Residuals in Exploratory Factor Analysis: New Proposals and a Comparison of Procedures. Structural Equation Modeling-A Multidisciplinary Journal, 29(4), 630-638. DOI: 10.1080/10705511.2021.2004543
    DOI de l'article: 10.1080/10705511.2021.2004543
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2022
    Tipus de publicació: Journal Publications
  • Paraules clau:

    Decision Sciences (Miscellaneous),Economics, Econometrics and Finance (Miscellaneous),Mathematics, Interdisciplinary Applications,Modeling and Simulation,Social Sciences, Mathematical Methods,Sociology and Political Science
    Parallel analysis
    Index
    Image theory
    Exploratory factor analysis
    Expected parameter change
    Doublets
    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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