New methods in multi-state models

The multi-state models may be considered as a generalization of the survival process where several events occur successively over time. The classical multi-state model describes the life history of an individual as moving through various states. Thus at any time, say t, the individual will be in one state. For a single individual, these states may describe whether the subject is healthy, diseased, diseased with complication or dead. Estimation of the transition probabilities in a non-homogeneous illness-death model is considered here. Traditionally, inference for such models is based on the Markov assumption. We review some of these results and propose new estimators, based on a less restrictive (non-Markov) approach.