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Springer International Publishing
Reference19 articles.
1. Bauer, D. J. & Curran, P. J. (2003). Distributional assumptions of growth mixture models: implications for overextraction of latent trajectory classes. Psychological Methods, 8(3), 338–363. https://doi.org/10.1037/1082-989X.8.3.338
2. Celeux, G., Forbes, F., Robert, C. P., & Titterington, D. M. (2006). Deviance information criteria for missing data models. Bayesian Analysis, 1, 651–673. https://doi.org/10.1214/06-ba122
3. Depaoli, S. (2013). Mixture class recovery in GMM under varying degrees of class separation: Frequentist versus Bayesian estimation. Psychological Methods, 18, 186–219. https://doi.org/10.1037/a0031609
4. Depaoli, S. (2014). The impact of inaccurate âinformativeâ priors for growth parameters in Bayesian growth mixture modeling. Structural Equation Modeling: A Multidisciplinary Journal, 21(2), 239–252. https://doi.org/10.1080/10705511.2014.882686
5. Frankfurt, S., Frazier, P., Syed, M., & Jung, K. R. (2016). Using group-based trajectory and growth mixture modeling to identify classes of change trajectories. The Counseling Psychologist, 44(5), 622–660. https://doi.org/10.1177/0011000016658097
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