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Identifying Bias in Social and Health Research: Measurement Invariance and Latent Mean Differences Using the Alignment Approach

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  • Ioannis Tsaousis

    (Department of Psychology, National and Kapodistrian University of Athens, 15784 Athens, Greece)

  • Fathima M. Jaffari

    (Education & Training Evaluation Commission (ETEC), Riyadh 12395, Saudi Arabia)

Abstract

When comparison among groups is of major importance, it is necessary to ensure that the measuring tool exhibits measurement invariance. This means that it measures the same construct in the same way for all groups. In the opposite case, the test results in measurement error and bias toward a particular group of respondents. In this study, a new approach to examine measurement invariance was applied, which was appropriately designed when a large number of group comparisons are involved: the alignment approach. We used this approach to examine whether the factor structure of a cognitive ability test exhibited measurement invariance across the 26 universities of the Kingdom of Saudi Arabia. The results indicated that the P-GAT subscales were invariant across the 26 universities. Moreover, the aligned factor mean values were estimated, and factor mean comparisons of every group’s mean with all the other group means were conducted. The findings from this study showed that the alignment procedure is a valuable method to assess measurement invariance and latent mean differences when a large number of groups are involved. This technique provides an unbiased statistical estimation of group means, with significance tests between group pairs that adjust for sampling errors and missing data.

Suggested Citation

  • Ioannis Tsaousis & Fathima M. Jaffari, 2023. "Identifying Bias in Social and Health Research: Measurement Invariance and Latent Mean Differences Using the Alignment Approach," Mathematics, MDPI, vol. 11(18), pages 1-15, September.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:18:p:4007-:d:1244584
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    References listed on IDEAS

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    1. Hanushek, Eric A. & Woessmann, Ludger, 2011. "The Economics of International Differences in Educational Achievement," Handbook of the Economics of Education, in: Erik Hanushek & Stephen Machin & Ludger Woessmann (ed.), Handbook of the Economics of Education, edition 1, volume 3, chapter 2, pages 89-200, Elsevier.
    2. Erik Hanushek & F. Welch (ed.), 2006. "Handbook of the Economics of Education," Handbook of the Economics of Education, Elsevier, edition 1, volume 1, number 1, June.
    3. Glewwe, Paul & Kremer, Michael, 2006. "Schools, Teachers, and Education Outcomes in Developing Countries," Handbook of the Economics of Education, in: Erik Hanushek & F. Welch (ed.), Handbook of the Economics of Education, edition 1, volume 2, chapter 16, pages 945-1017, Elsevier.
    4. Erik Hanushek & F. Welch (ed.), 2006. "Handbook of the Economics of Education," Handbook of the Economics of Education, Elsevier, edition 1, volume 2, number 2, June.
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    Cited by:

    1. Alexander Robitzsch, 2024. "Examining Differences of Invariance Alignment in the Mplus Software and the R Package Sirt," Mathematics, MDPI, vol. 12(5), pages 1-16, March.
    2. Alexander Robitzsch, 2025. "Standard Error Estimation in Invariance Alignment," Mathematics, MDPI, vol. 13(12), pages 1-14, June.
    3. Alexander Robitzsch, 2025. "Comparing Robust Haberman Linking and Invariance Alignment," Stats, MDPI, vol. 8(1), pages 1-15, January.

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