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

  • Identification data

    Identifier: imarina:9243511
    Authors:
    Ferrando, Pere JHernandez-Dorado, AnaLorenzo-Seva, Urbano
    Abstract:
    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.
  • Others:

    Author, as appears in the article.: Ferrando, Pere J; Hernandez-Dorado, Ana; Lorenzo-Seva, Urbano
    Department: Psicologia
    URV's Author/s: Ferrando Piera, Pere Joan / Hernández Dorado, Ana / Lorenzo Seva, Urbano
    Keywords: Parallel analysis Index Image theory Exploratory factor analysis Expected parameter change Doublets Correlated residuals
    Abstract: 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.
    Thematic Areas: 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
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: ana.hernandez@urv.cat urbano.lorenzo@urv.cat perejoan.ferrando@urv.cat
    Author identifier: 0000-0001-5369-3099 0000-0002-3133-5466
    Record's date: 2024-10-12
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://www.tandfonline.com/doi/full/10.1080/10705511.2021.2004543
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Structural Equation Modeling-A Multidisciplinary Journal. 29 (4): 630-638
    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
    Article's DOI: 10.1080/10705511.2021.2004543
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2022
    Publication Type: Journal Publications
  • Keywords:

    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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