Using Bayesian Statistics for Modeling PTSD through Latent Growth Mixture Modeling: Implementation and Discussion

We used latent growth mixture modeling (LGMM)  to estimate PTSD trajectories across four years that followed a traumatic burn. We demonstrate and compare results from traditional (maximum likelihood) and Bayesian estimation using priors. Further, we discuss where priors come from and how to define them in the estimation process.

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