Testing measurement invariance across groups: applications in cross-cultural research.

By T. Milfont, Ronald Fischer. 2010

1,569 citations recorded by the source corpus.

Researchers often compare groups of individuals on psychological variables. When comparing groups an assumption is made that the instrument measures the same psychological construct in all groups. If this assumption holds, the comparisons are valid and differences/similarities between groups can be meaningfully interpreted. If this assumption does not hold, comparisons and interpretations are not fully meaningful. The establishment of measurement invariance is a prerequisite for meaningful comparisons across groups. This paper first reviews the importance of equivalence in psychological research, and then the main theoretical and methodological issues regarding measurement invariance within the framework of confirmatory factor analysis. A step-by-step empirical example of measurement invariance testing is provided along with syntax examples for fitting such models in LISREL

Subfields: Management Science and Operations Research, Social Psychology, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/a3d4e94070ac500a31404953ec93c391af6ae754

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In Management Science and Operations Research

In Social Psychology

In Sociology and Political Science

Citations in the corpus

Environmental Behavior in Cross-National Perspective (2017, background): “It is satisfied if the basic model structure and loading weights are invariant across groups, indicating that participants from different countries conceptualize the constructs and respond to the items in a similar way (Milfont & Fischer, 2010; Vandenberg & Lance, 2000).”
A Global Look at Time (2014, background): “If this equivalence assumption does not hold, comparisons and interpretations are not fully meaningful (Milfont & Fischer, 2010; van de Vijver & Leung, 1997).”
Testing for Measurement Invariance: Does your measure mean the same thing for different participants? (2018, methodology): “Measurement Invariance Testing: Multigroup Confirmatory Factor Analysis To test measurement invariance across participants from various groups, researchers use a statistical technique called “multigroup confirmatory factory analysis” (CFA; Milfont & Fischer, 2015).”
Differences in Emotional Labor Across Cultures: A Comparison of Chinese and U.S. Service Workers (2013, neutral): “That is, differences in the magnitude of factor loadings suggest that the contribution of indicators to a latent construct is different, but such a difference does not mean that the substantive meaning of the construct is not comparable across groups (Byrne et al. 1989; Milfont and Fischer 2010).”
Cross-Cultural Evidence for Spatial Bias in Beliefs About the Severity of Environmental Problems (2014, background): “It is satisfied if the basic model structure and loading weights are invariant across groups, indicating that participants from different countries conceptualize the constructs and respond to the items in the same way (Milfont & Fischer, 2010; Vandenberg & Lance, 2000).”
Evaluating the Perceived Stress Scale among UK university students: implications for stress measurement and management (2019, background): “Satisfaction of these criteria indicates that the PSS10 is not biased in relation to its factor structure, factor loadings, or intercepts (Milfont and Fischer 2010).”