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Measurement Invariance: Testing for It and Explaining Why It is Absent


Meitinger, Katharina; Davidov, Eldad; Schmidt, Peter; Braun, Michael (2020). Measurement Invariance: Testing for It and Explaining Why It is Absent. Survey Research Methods, 14(4):345-349.

Abstract

There has been a significant increase in cross-national and longitudinal data production in social science research in recent decades. Before drawing substantive conclusions based on cross-national and longitudinal survey data, researchers need to assess whether the constructs are measured in the same way across countries and time-points. If cross-national data are not tested for comparability, researchers risk confusing methodological artifacts as “real” substantive differences across countries. However, researchers often find it particularly difficult to establish the highest level of measurement invariance, that is, exact scalar invariance. When measurement invariance is rejected, it is crucial to understand why this was the case and to address its absence with approaches, such as alignment optimization or Bayesian structural equation modeling.

Abstract

There has been a significant increase in cross-national and longitudinal data production in social science research in recent decades. Before drawing substantive conclusions based on cross-national and longitudinal survey data, researchers need to assess whether the constructs are measured in the same way across countries and time-points. If cross-national data are not tested for comparability, researchers risk confusing methodological artifacts as “real” substantive differences across countries. However, researchers often find it particularly difficult to establish the highest level of measurement invariance, that is, exact scalar invariance. When measurement invariance is rejected, it is crucial to understand why this was the case and to address its absence with approaches, such as alignment optimization or Bayesian structural equation modeling.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Sociology
08 Research Priority Programs > Social Networks
Dewey Decimal Classification:300 Social sciences, sociology & anthropology
Scopus Subject Areas:Social Sciences & Humanities > Education
Uncontrolled Keywords:Measurement invariance, comparability, bias, approximate measurement invariance, alignment, BSEM
Language:English
Date:10 October 2020
Deposited On:24 Nov 2020 10:24
Last Modified:23 Dec 2020 04:38
Publisher:European Survey Research Association
ISSN:1864-3361
Additional Information:Meitinger, K., Davidov, E., Schmidt, P., & Braun, M. (2020). Measurement Invariance: Testing for It and Explaining Why It is Absent. Survey Research Methods, 14(4), 345-349. https://doi.org/10.18148/srm/2020.v14i4.7655
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.18148/srm/2020.v14i4.7655
Related URLs:https://www.zora.uzh.ch/id/eprint/194355/

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