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Abstract:
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In this talk I will discuss models for recurrent event models and longitudinal markers which involve state-space components. These components may appear in the modeling of frailty or random effects or they may appear as an underlying unobserved process partly governing and connecting the behavior of the marker and recurrent event processes. Most current models relating marker and recurrent event processes in survival analysis and reliability settings do not involve state-space components, though in the econometric and financial settings, such models appear are more common. It is hoped that through the discussions in this session, we will gain more insights of the use of such state-space models for modeling of data in the survival and reliability settings. Inference for such models, notably those using sequential Monte Carlo (SMC) methods, will also be discussed.
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