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?

Answer

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

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

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