A Case Study of the Application of a Multilevel Growth Curve Model and the Prediction of Health Trajectories


This case study provides guidance on the application of a multilevel growth curve model and the prediction of health trajectories. Using our secondary data analysis as an example, we introduce definitions of the multilevel growth curve model, random intercept and slope, and the intraclass correlation coefficient. We discuss time centering and time metrics, marginal effects for drawing frailty trajectories, as well as multiple imputation for handling missing values.

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