GÉGOUT-PETIT, Anne; COMMENGES, Daniel

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GÉGOUT-PETIT, Anne
Institut de Mathématiques de Bordeaux [IMB]
Epidémiologie, santé publique et développement

COMMENGES, Daniel
Epidémiologie, santé publique et développement

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Statistical Modelling and Inference in Life Sciences, 2005-09-29, Potsdam.

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We consider first the mixed discrete-continuous scheme of observation in multistate models; this is a classical pattern in epidemiology because very often clinical status is assessed at discrete visit times while times of death or other events are observed exactly. A heuristic likelihood can be written for such models, at least for Markov models; however, a formal proof is not easy and has not been given yet. We present a general class of possibly non-Markov multistate models which can be represented naturally as multivariate counting processes.We give a rigorous derivation of the likelihood based on applying Jacod's formula for the full likelihood and taking conditional expectation for the observed likelihood. A local description of the likelihood allows us to extend the result to a more general coarsening observation scheme proposed by Commenges & G´egout-Petit. The approach is illustrated by considering models for dementia, institutionalization and death< Réduire

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coarsening

counting processes

dementia

interval-censoring

likelihood

Markov models

multi state models

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Likelihood Formulae for generally coarsened observations from Multistate models

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