What are the differences between “Mixed Effects Modelling” and “Latent Growth Modelling”?

I’m decently familiar with mixed effects models (MEM), but a colleague recently asked me how it compares to latent growth models (LGM). I did a bit of googling, and it seems that LGM is a variant of structural equation modelling that is applied to circumstances where repeated measures are obtained within each level of at least one random effect, thus making Time a fixed effect in the model. Otherwise, MEM and LGM seem pretty similar (eg. they both permit exploration of different covariance structures, etc).

Am I correct that LGM is conceptually a special case of MEM, or are there differences between the two approaches with respect to their assumptions or capacity to evaluate different types of theories?


LGM can be translated to a MEM and vice versa, so these models are actually the same. I discuss the comparison in the chapter on LGM in my multilevel book, the draft of that chapter is on my homepage at http://www.joophox.net/papers/chap14.pdf

Source : Link , Question Author : Mike Lawrence , Answer Author : whuber

Leave a Comment