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- W4252273997 abstract "Abstract. 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 & Gégout-Petit. The approach is illustrated by considering models for dementia, institutionalization and death." @default.
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- W4252273997 date "2007-06-01" @default.
- W4252273997 modified "2023-10-18" @default.
- W4252273997 title "Likelihood for Generally Coarsened Observations from Multistate or Counting Process Models" @default.
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- W4252273997 doi "https://doi.org/10.1111/j.1467-9469.2007.00518.x" @default.
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