The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Testing factorial invariance across groups: A reconceptualization and proposed new method
Abstract
Many cross-cultural researchers are concerned with factorial invariance; that is, with whether or not members of different cultures associate survey items, or similar measures, with similar constructs. Researchers usually test items for factorial invariance using confirmatory factor analysis (CFA). CFA, however, poses certain problems that must be dealt with. Primary among them is standardization, the process that assigns units of measurement to the constructs (latent variables). Two standardization procedures and several minor variants have been reported in the literature, but using these procedures when testing for factorial invariance can lead to inaccurate results. In this paper we review basic theory, and propose an extension of Byrne, Shavelson, and Muthgn’s (1989) procedure for identifying non-invariant items. The extended procedure solves the standardization problem by performing a systematic comparison of all pairs of factor loadings across groups. A numerical example based upon a large published data set is presented to illustrate the utility of the new procedure, particularly with regard to partial factorial invariance.
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Cites
Measurement Invariance, Factor Analysis and Factorial Invariance
Meredith, W. (1993) · Psychometrika · doi:10.1007/bf02294825 · Cited by 4,536
Byrne, B. M., Shavelson, R. J., & Muthén, B. (1989) · Psychological Bulletin · doi:10.1037//0033-2909.105.3.456 · Cited by 4,115
Diagnosing measurement equivalence in cross-national research.
Mullen, M. R. (1995) · Journal of International Business Studies · doi:10.1057/palgrave.jibs.8490187 · Cited by 863
Cited by
Vandenberg, R. J., & Lance, C. E. (2000) · Organizational Research Methods · doi:10.1177/109442810031002 · Cited by 7,997
Putnick, D. L., & Bornstein, M. H. (2016) · Developmental Review · doi:10.1016/j.dr.2016.06.004 · Cited by 4,369
“…turn of the 21st century, methodologists increasingly directed attention to the significance of measurement invariance, especially within a structural equation modeling framework (Cheung & Rensvold, 1999, 2002; Little, 2000; Rensvold & Cheung, 1998; Steenkamp & Baumgartner, 1998; Vandenberg, 2002).”
BackgroundMethodFlourishing Across Europe: Application of a New Conceptual Framework for Defining Well-Being
Huppert, F. A., & So, T. T. C. (2013) · Social Indicators Research · doi:10.1007/s11205-011-9966-7 · Cited by 1,864
Antonakis, J., Avolio, B. J., & Sivasubramaniam, N. (2003) · The Leadership Quarterly · doi:10.1016/s1048-9843(03)00030-4 · Cited by 1,533
The Motivation at Work Scale: Validation Evidence in Two Languages
Gagné, M., Forest, J., Gilbert, M.-H., Aubé, C., Morin, E., & Malorni, A. (2010) · Educational and Psychological Measurement · doi:10.1177/0013164409355698 · Cited by 770
Metadata
- Authors
- Cheung, G.
- Venue
- Journal of Management
- Publisher
- SAGE Publications
- Published
- 1999
- Volume
- 25
- Issue
- 1
- Pages
- 1-27
- ISSN
- 0149-2063 (ISSN-L)
- OpenAlex
- W1899874729
- Cited by
- 726
- References
- 3
- FWCI
- 11.73
- Type
- journal article
- Language
- en
- Open access
- closed
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- Cheung, G. (1999). Testing factorial invariance across groups: A reconceptualization and proposed new method. Journal of Management. https://doi.org/10.1016/s0149-2063(99)80001-4
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