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Journal Articles Lifetime Data Analysis Year : 2003

A latent process model for joint modeling of events and marker.

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Abstract

The paper formulates joint modeling of a counting process and a sequence of longitudinal measurements, governed by a common latent stochastic process. The latent process is modeled as a function of explanatory variables and a Brownian motion process. The conditional likelihood given values of the latent process at the measurement times, has been drawn using Brownian bridge properties; then integrating over all possible values of the latent process at the measurement times leads to the desired joint likelihood. An estimation procedure using joint likelihood and a numerical optimization is described. The method is applied to the study of cognitive decline and Alzheimer's disease.
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Dates and versions

inserm-00262051 , version 1 (10-03-2008)

Identifiers

  • HAL Id : inserm-00262051 , version 1
  • PUBMED : 15000408

Cite

Reza Hashemi, Hélène Jacqmin-Gadda, Daniel Commenges. A latent process model for joint modeling of events and marker.. Lifetime Data Analysis, 2003, 9 (4), pp.331-43. ⟨inserm-00262051⟩

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