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Multiple Imputation of missing values in exploratory factor analysis of multidimensional scales: estimating latent trait scores

  • Identification data

    Identifier: imarina:9286576
    Authors:
    Lorenzo-Seva, UrbanoVan Ginkel, Joost R.
    Abstract:
    Researchers frequently have to analyze scales in which some participants have failed to respond to some items. In this paper we focus on the exploratory factor analysis of multidimensional scales (i.e., scales that consist of a number of subscales) where each subscale is made up of a number of Liken-type items, and the aim of the analysis is to estimate participants' scores on the corresponding latent traits. We propose a new approach to deal with missing responses in such a situation that is based on (1) multiple imputation of non-responses and (2) simultaneous rotation of the imputed datasets. We applied the approach in a real dataset where missing responses were artificially introduced following a real pattern of non-responses, and a simulation study based on artificial datasets. The results show that our approach (specifically, Hot-Deck multiple imputation followed of Consensus Promin rotation) was able to successfully compute factor score estimates even for participants that have missing data.
  • Others:

    Author, as appears in the article.: Lorenzo-Seva, Urbano; Van Ginkel, Joost R.;
    Department: Psicologia
    URV's Author/s: Lorenzo Seva, Urbano
    Keywords: Variables Predictive mean matching imputation Parameters Optimal agreement Oblique factor rotation Multiple imputation Missing data Loading matrices Hot-deck imputation Factor scores Exploratory factor analysis Consensus rotation
    Abstract: Researchers frequently have to analyze scales in which some participants have failed to respond to some items. In this paper we focus on the exploratory factor analysis of multidimensional scales (i.e., scales that consist of a number of subscales) where each subscale is made up of a number of Liken-type items, and the aim of the analysis is to estimate participants' scores on the corresponding latent traits. We propose a new approach to deal with missing responses in such a situation that is based on (1) multiple imputation of non-responses and (2) simultaneous rotation of the imputed datasets. We applied the approach in a real dataset where missing responses were artificially introduced following a real pattern of non-responses, and a simulation study based on artificial datasets. The results show that our approach (specifically, Hot-Deck multiple imputation followed of Consensus Promin rotation) was able to successfully compute factor score estimates even for participants that have missing data.
    Thematic Areas: Saúde coletiva Revistas ciencias del comportamiento Psychology, multidisciplinary Psychology (miscellaneous) Psychology (all) Psychology Psicología Medicina i General psychology Educação Ciencias sociales
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: urbano.lorenzo@urv.cat
    Author identifier: 0000-0001-5369-3099
    Record's date: 2024-09-07
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://revistas.um.es/analesps/article/view/analesps.32.2.215161
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Anales De Psicologia. 32 (2): 596-608
    APA: Lorenzo-Seva, Urbano; Van Ginkel, Joost R.; (2016). Multiple Imputation of missing values in exploratory factor analysis of multidimensional scales: estimating latent trait scores. Anales De Psicologia, 32(2), 596-608. DOI: 10.6018/analesps.32.2.215161
    Article's DOI: 10.6018/analesps.32.2.215161
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2016
    Publication Type: Journal Publications
  • Keywords:

    Psychology,Psychology (Miscellaneous),Psychology, Multidisciplinary
    Variables
    Predictive mean matching imputation
    Parameters
    Optimal agreement
    Oblique factor rotation
    Multiple imputation
    Missing data
    Loading matrices
    Hot-deck imputation
    Factor scores
    Exploratory factor analysis
    Consensus rotation
    Saúde coletiva
    Revistas ciencias del comportamiento
    Psychology, multidisciplinary
    Psychology (miscellaneous)
    Psychology (all)
    Psychology
    Psicología
    Medicina i
    General psychology
    Educação
    Ciencias sociales
  • Documents:

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