Growth Mixture Models in the Structural Equation Modeling Versus the Multilevel Modeling Framework

The performance of linear growth mixture models (GMMs) estimated in the multilevel modeling (MLM) framework and the structural equation modeling (SEM) framework in Mplus is examined. Empirical analyses conducted using data from the Early Childhood Longitudinal Study - Kindergarten Class of 1998-1999 (ECLS-K) led to different estimates of a 2-class linear GMM when estimated in the MLM versus the SEM frameworks via Mplus. A simulation study was conducted under varying conditions of sample size and class separation to better understand when differences in model fit and parameter estimates emerge. Results suggested the frameworks yielded comparable model fit information and parameter estimates when class separation was large; however, differences emerged as class separation decreased with the MLM estimation routine tending to outperform the SEM estimation routine. Overall, these findings highlight the importance of considering the estimation framework when estimating linear GMMs in Mplus.