CiteWeb id: 20140001174

CiteWeb score: 217

This article discusses alternatives to single-step mixture modeling. A 3-step method for latent class predictor variables is studied in several different settings, including latent class analysis, latent transition analysis, and growth mixture modeling. It is explored under violations of its assumptions such as with direct effects from predictors to latent class indicators. The 3-step method is also considered for distal variables. The Lanza, Tan, and Bray (2013) method for distal variables is studied under several conditions including violations of its assumptions. Standard errors are also developed for the Lanza method because these were not given in Lanza et al. (2013).Full text HTMLPDFKeywords3-step estimation, distal outcomes, latent class predictors, mixture modeling, MplusRelated articlesView all related articlesAdd to shortlist Link Permalink

The publication "Auxiliary Variables in Mixture Modeling: Three-Step Approaches Using Mplus" is placed in the Top 10000 in 2014.
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