G. Bull

Forecasting Repeated-Measures Trajectories Using Nonlinear Mixed-Effects Models: A Comparison of Population-Averaged, Subject-Specific, and Autocorrelation-Based Predictions

Nonlinear mixed-effects models (NLMMs) provide a flexible framework for modeling repeated-measures trajectories. However, how best to forecast future observations, especially at ages well beyond those represented in the data, remains relatively underexamined. In this study, we develop a Chapman–Richards NLMM with a spa...