Identifying Trajectories of Periodontitis Progression Using Censored Growth Mixture Modeling

Growth Mixture Modeling (GMM), widely used to identify subpopulations with unique trajectories, is underutilized in dental research. Using a big longitudinal dataset collected over 8 years, we applied censored GMM to examine periodontitis. Results revealed distinct trajectories, but demographics failed to fully predict class membership, prompting exploration of psychological predictors.