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Simultaneous latent-class analysis across groups (SLCAG) is an extension of the standard latent-class (LC) model (Latent Class Model) for the examination of measurement equivalence/invariance (Measurement Invariance). It can be used to compare the latent structure derived from a set of discrete item responses between multiple groups, for example, between males and females; between Japanese, Americans, and Dutch; between young and old; and between ill and healthy. Whereas the more commonly used multigroup confirmatory factor analysis (MCFA) (Factorial Invariance) assumes that the underlying latent variables are continuous, SLCAG treats the latent variables (Latent Variables) either as nominal, for example, to identify a typological classification from a given set of categorical indicators, or as ordinal, for example, to investigate the scalability of a set of categorical indicators. These two specifications are sometimes referred as...
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References
Clogg, C. C., & Goodman, L. A. (1985). Simultaneous latent structural analysis in several groups. In N. B. Tuma (Ed.), Sociological methodology (pp. 81–110). San Francisco: Jossey-Bass Publishers.
Eid, M., Langeheine, R., & Diener, E. (2003). Comparing typological structures across cultures by multigroup latent class analysis. A primer. Journal of Cross-Cultural Psychology, 34, 195–210.
Goodman, L. A. (1974). Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika, 61, 215–231.
Haberman, S. J. (1979). Analysis of qualitative data: Vol. 2 New Developments. New York: Academic.
Hagenaars, J. A. (1990). Categorical longitudinal data – Loglinear analysis of panel, trend and cohort data. Newbury Park, CA: Sage.
Hagenaars, J. A., & McCutcheon, A. L. (2002). Applied latent class analysis. Cambridge, UK: Cambridge University Press.
Kankaraš, M., Moors, G., & Vermunt, J. K. (2010). Testing for measurement invariance with latent class analysis. In E. Davidov, P. Schmidt, & J. Billiet (Eds.), Cross-cultural analysis: Methods and applications (pp. 359–384). New York: Routledge.
Lazarsfeld, P. F., & Henry, N. W. (1968). Latent structure analysis. Boston: Houghton Mifflin.
McCutcheon, A. L., & Hagenaars, J. A. (1997). Comparative social research with multi-sample latent class models. In J. Rost & R. Langeheine (Eds.), Applications of latent trait and latent class models in the social sciences (pp. 266–277). Münster, Germany: Waxmann.
Moors, G. (2004). Facts and artefacts in the comparison of attitudes among ethnic minorities. A multi-group latent class structure model with adjustment for response style behaviour. European Sociological Review, 20, 303–320.
Muthén, L. K., & Muthén, B. O. (2006). Mplus user’s guide (4th ed.). Los Angeles: Muthén and Muthén.
Rabe-Hesketh, S., Skrondal, A., & Pickles, A. (2004). GLLAMM Manual. U.C. Berkeley Division of Biostatistics Working Paper Series (Working Paper 160).
Vermunt, J. K. (1997). LEM 1.0: A general program for the analysis of categorical data. Tilburg, The Netherlands: Tilburg University.
Vermunt, J. K., & Magidson, J. (2005). Factor analysis with categorical indicators: A comparison between traditional and latent class approaches. In A. Van der Ark, M. A. Croon, & K. Sijtsma (Eds.), New developments in categorical data analysis for the social and behavioral sciences (pp. 41–62). Mahwah, NJ: Erlbaum.
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Kankaraš, M., Vermunt, J.K. (2014). Simultaneous Latent-Class Analysis Across Groups. In: Michalos, A.C. (eds) Encyclopedia of Quality of Life and Well-Being Research. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0753-5_2711
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