Statistical Modelling 9 (2009), 345–360
Estimating life expectancy of demented and institutionalized subjects from
interval-censored observations of a multi-state model
Pierre Joly
INSERM, U897, Epidémiologie et Biostatistique
Université de Bordeaux 2
146 rue Léo Saignat
F–33076 Bordeaux cedex
France
eMail: pierre.joly@isped.u-bordeaux2.fr
Cécile Durand
Institut de veille sanitaire
France
Catherine Helmer
Université Victor Ségalen Bordeaux 2 ISPED
France
Daniel Commenges
Université Victor Ségalen Bordeaux 2 ISPED
France
Abstract:
We consider the problem of estimating life expectancy of demented and
institutionalized subjects from interval-censored observations. A mixed
discrete-continuous scheme of observation is a classical pattern in
epidemiology because very often clinical status is assessed at discrete
visit times while times of death or other events can be exactly observed.
In this work, we jointly modelled dementia, institutionalization and
death from data of a cohort study. Due to discrete time observations,
it may happen that a subject developed dementia or was institutionalized
between the last visit and the death. Consequently, there is an
uncertainty about the precise number of diseased or institutionalized
subjects. Moreover, the time of onset of dementia is interval censored.
We use a penalized likelihood approach for estimating the transition
intensities of the multi-state model. With these estimators, incidence
and life expectancy can be computed easily. This approach deals with
incomplete data due to the presence of left truncation and interval
censoring. It can be generalized to take explanatory variables into
account. We illustrate this approach by applying this model to the
analysis of a large cohort study on cerebral ageing.
Keywords:
dementia; institutionalization; interval censoring;
life expectancy; multi-state model; penalized likelihood
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