Auxiliary variables in mixture modeling: A 3-step approach using Mplus. Mplus Web Notes

This paper 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 et al. (2013) method for distal variables is studied under several conditions including violations of its assumptions. Standard errors are also developed for the Lanza method since these were not given in Lanza et al. (2013). 2