Modelling growth and decline in lung function in Duchenne's muscular dystrophy with an augmented linear mixed effects model

Longitudinal modelling of lung function in Duchenne's muscular dystrophy is complicated by a mixture of both growth and decline in lung function within each subject, an unknown point of separation between these phases and significant heterogeneity between individual trajectories. Linear mixed effects models can be used, assuming a single changepoint for all cases; however, this assumption may be incorrect. The paper describes an extension of linear mixed effects modelling in which random changepoints are integrated into the model as parameters and estimated by using a stochastic EM algorithm. We find that use of this 'mixture modelling' approach improves the fit significantly.