Introduction

This is a living document, recording my current state of knowledge about growth mixture models (and related classes of models) and how to fit them using R and Stan.

The motivation for this report is being able to fit growth curve models and latent class growth curve models using R (R Core Team 2021) and Stan (Guo et al. 2020). There are various packages available for fitting growth models, but not necessarily for doing so in the flexible Bayesian way.

Canonically, the main package to use in R for this purpose is lcmm (Proust-Lima, Philipps, and Liquet 2017) and the corresponding plugin in Stata is traj (Jones and Nagin 2013).

References

Guo, Jiqiang, Jonah Gabry, Ben Goodrich, and Sebastian Weber. 2020. Rstan: R Interface to Stan. https://CRAN.R-project.org/package=rstan.

Jones, Bobby L., and Daniel S. Nagin. 2013. “A Note on a Stata Plugin for Estimating Group-Based Trajectory Models.” Sociological Methods & Research 42 (4): 608–13. https://doi.org/10.1177/0049124113503141.

Proust-Lima, Cécile, Viviane Philipps, and Benoit Liquet. 2017. “Estimation of Extended Mixed Models Using Latent Classes and Latent Processes: The R Package lcmm.” Journal of Statistical Software 78 (2): 1–56. https://doi.org/10.18637/jss.v078.i02.

R Core Team. 2021. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.