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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
social sciences
Measurement invariance in the social sciences: Historical development, methodological challenges, state of the art, and future perspectives
Social Science Research, Volume 110, Article 102805, Year 2023
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Description
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. © 2022 Elsevier Inc.
Authors & Co-Authors
De Roover, Kim
Netherlands, Tilburg
Tilburg University
Belgium, Leuven
Ku Leuven
Muthén, Bengt O.
United States, Fairfield
University of California
Rudnev, Maksim G.
Canada, Waterloo
University of Waterloo
Schmidt, Peter Fritz
Germany, Giessen
Justus-liebig-universität Gießen
Germany, Mainz
Johannes Gutenberg-universität Mainz
van de Schoot, Rens A.G.J.
Netherlands, Utrecht
Universiteit Utrecht
Statistics
Citations: 41
Authors: 5
Affiliations: 15
Identifiers
Doi:
10.1016/j.ssresearch.2022.102805
ISSN:
0049089X
Study Design
Cross Sectional Study
Study Approach
Quantitative