Measurement invariance in the social sciences: Historical development, methodological challenges, state of the art, and future perspectives

Heinz Leitgöb; Daniel Seddig; Tihomir Asparouhov; Dorothée Behr; Eldad Davidov; Kim De Roover; Suzanne Jak; Katharina Meitinger; Natalja Menold; Bengt Muthén; Maksim Rudnev; Peter Schmidt; Rens van de Schoot

doi:10.1016/j.ssresearch.2022.102805

Measurement invariance in the social sciences: Historical development, methodological challenges, state of the art, and future perspectives

Heinz Leitgöb^*, Daniel Seddig, Tihomir Asparouhov, Dorothée Behr, Eldad Davidov, Kim De Roover, Suzanne Jak, Katharina Meitinger, Natalja Menold, Bengt Muthén, Maksim Rudnev, Peter Schmidt, Rens van de Schoot

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

This review summarizes the current state of the art of statistical and (survey) methodological research on measurement (non)invariance, which is considered a core challenge for the comparative social sciences. After outlining the historical roots, conceptual details, and standard procedures for measurement invariance testing, the paper focuses in particular on the statistical developments that have been achieved in the last 10 years. These include Bayesian approximate measurement invariance, the alignment method, measurement invariance testing within the multilevel modeling framework, mixture multigroup factor analysis, the measurement invariance explorer, and the response shift-true change decomposition approach. Furthermore, the contribution of survey methodological research to the construction of invariant measurement instruments is explicitly addressed and highlighted, including the issues of design decisions, pretesting, scale adoption, and translation. The paper ends with an outlook on future research perspectives.

Original language	English
Article number	102805
Number of pages	30
Journal	Social Science Research
Volume	110
DOIs	https://doi.org/10.1016/j.ssresearch.2022.102805
Publication status	Published - Feb 2023

Bibliographical note

Funding Information:
This work was partly supported by the Dutch Research Council (NWO) , project number VI.Vidi.201.009, awarded to Suzanne Jak.

Publisher Copyright:
© 2022 Elsevier Inc.

Funding

This work was partly supported by the Dutch Research Council (NWO) , project number VI.Vidi.201.009, awarded to Suzanne Jak.

Funders	Funder number
Dutch Research Council (NWO)	VI.Vidi.201.009

Keywords

Comparative research
Item bias
Measurement invariance
Multiple group confirmatory factor analysis
Noninvariance detection
Scale construction

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10.1016/j.ssresearch.2022.102805

1-s2.0-S0049089X22001168-mainFinal published version, 2.41 MBLicence: Taverne

Cite this

Leitgöb, H., Seddig, D., Asparouhov, T., Behr, D., Davidov, E., De Roover, K., Jak, S., Meitinger, K., Menold, N., Muthén, B., Rudnev, M., Schmidt, P., & van de Schoot, R. (2023). Measurement invariance in the social sciences: Historical development, methodological challenges, state of the art, and future perspectives. Social Science Research, 110, Article 102805. https://doi.org/10.1016/j.ssresearch.2022.102805

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title = "Measurement invariance in the social sciences: Historical development, methodological challenges, state of the art, and future perspectives",

abstract = "This review summarizes the current state of the art of statistical and (survey) methodological research on measurement (non)invariance, which is considered a core challenge for the comparative social sciences. After outlining the historical roots, conceptual details, and standard procedures for measurement invariance testing, the paper focuses in particular on the statistical developments that have been achieved in the last 10 years. These include Bayesian approximate measurement invariance, the alignment method, measurement invariance testing within the multilevel modeling framework, mixture multigroup factor analysis, the measurement invariance explorer, and the response shift-true change decomposition approach. Furthermore, the contribution of survey methodological research to the construction of invariant measurement instruments is explicitly addressed and highlighted, including the issues of design decisions, pretesting, scale adoption, and translation. The paper ends with an outlook on future research perspectives.",

keywords = "Comparative research, Item bias, Measurement invariance, Multiple group confirmatory factor analysis, Noninvariance detection, Scale construction",

author = "Heinz Leitg{\"o}b and Daniel Seddig and Tihomir Asparouhov and Doroth{\'e}e Behr and Eldad Davidov and {De Roover}, Kim and Suzanne Jak and Katharina Meitinger and Natalja Menold and Bengt Muth{\'e}n and Maksim Rudnev and Peter Schmidt and {van de Schoot}, Rens",

note = "Funding Information: This work was partly supported by the Dutch Research Council (NWO) , project number VI.Vidi.201.009, awarded to Suzanne Jak. Publisher Copyright: {\textcopyright} 2022 Elsevier Inc.",

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doi = "10.1016/j.ssresearch.2022.102805",

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Leitgöb, H, Seddig, D, Asparouhov, T, Behr, D, Davidov, E, De Roover, K, Jak, S, Meitinger, K, Menold, N, Muthén, B, Rudnev, M, Schmidt, P & van de Schoot, R 2023, 'Measurement invariance in the social sciences: Historical development, methodological challenges, state of the art, and future perspectives', Social Science Research, vol. 110, 102805. https://doi.org/10.1016/j.ssresearch.2022.102805

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AU - Leitgöb, Heinz

AU - Seddig, Daniel

AU - Asparouhov, Tihomir

AU - Behr, Dorothée

AU - Davidov, Eldad

AU - De Roover, Kim

AU - Jak, Suzanne

AU - Meitinger, Katharina

AU - Menold, Natalja

AU - Muthén, Bengt

AU - Rudnev, Maksim

AU - Schmidt, Peter

AU - van de Schoot, Rens

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Measurement invariance in the social sciences: Historical development, methodological challenges, state of the art, and future perspectives

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