The Vuong-Lo-Mendell-Rubin Test for latent class and latent profile analysis: A note on the different implementations in Mplus and LatentGOLD
Vermunt,J.K.
Vermunt,J.K.
Abstract
Mplus and LatentGOLD implement the Vuong-Lo-Mendell-Rubin test (comparing models with K and K + 1 latent classes) in slightly differ manners. While LatentGOLD uses the formulae from Vuong (1989; https://doi.org/10.2307/1912557), Mplus replaces the standard parameter variancecovariance matrix by its robust version. Our small simulation study showed why such a seemingly small difference may sometimes yield rather different results. The main finding is that the Mplus approximation of the distribution of the likelihood -ratio statistic is much more data dependent than the LatentGOLD one. This data dependency is stronger when the true model serves as the null hypothesis (H0) with K classes than when it serves as the alternative hypothesis (H1) with K + 1 classes, and it is also stronger for low class separation than for high class separation. Another important finding is that neither of the two implementations yield uniformly distributed p -values under the correct null hypothesis, indicating this test is not the best model selection tool in mixture modeling.
Description
Date
2024
Journal Title
Journal ISSN
Volume Title
Publisher
Research Projects
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Journal Issue
Keywords
VLMR test, Class enumeration, Likelihood-ratio test, Mixture modeling, Nested models
Citation
Vermunt, J K 2024, 'The Vuong-Lo-Mendell-Rubin Test for latent class and latent profile analysis : A note on the different implementations in Mplus and LatentGOLD', Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, vol. 20, no. 1, pp. 72-83. https://doi.org/10.5964/meth.12467