Piecewise transition models with random effects for unequally spaced longitudinal measurements

In this paper, we consider the analysis of unequally spaced longitudinal data using transition regression models with random effects. Diffusion as well as stabilization processes will be discussed, but our main focus will be on the latter. The initial conditions problem, which usually arises in transition models with random effects, is addressed. The usefulness of the proposed model is assessed on a large database of longitudinal haemoglobin values collected from blood donations by a Dutch private organization.

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