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Lifetime Data Analysis

, Volume 20, Issue 4, pp 495–513 | Cite as

A competing risks approach for nonparametric estimation of transition probabilities in a non-Markov illness-death model

  • Arthur Allignol
  • Jan BeyersmannEmail author
  • Thomas Gerds
  • Aurélien Latouche
Article

Abstract

Competing risks model time to first event and type of first event. An example from hospital epidemiology is the incidence of hospital-acquired infection, which has to account for hospital discharge of non-infected patients as a competing risk. An illness-death model would allow to further study hospital outcomes of infected patients. Such a model typically relies on a Markov assumption. However, it is conceivable that the future course of an infected patient does not only depend on the time since hospital admission and current infection status but also on the time since infection. We demonstrate how a modified competing risks model can be used for nonparametric estimation of transition probabilities when the Markov assumption is violated.

Keywords

Left-truncation Bivariate survival Nosocomial infection  Markov assumption Multi-state model 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Arthur Allignol
    • 1
    • 3
  • Jan Beyersmann
    • 2
    • 3
    Email author
  • Thomas Gerds
    • 4
  • Aurélien Latouche
    • 5
  1. 1.Freiburg Centre for Data Analysis and ModellingUniversity of FreiburgFreiburgGermany
  2. 2.Institute of StatisticsUniversity of UlmUlmGermany
  3. 3.Institute of Medical Biometry and Medical InformaticsUniversity Medical Center FreiburgFreiburgGermany
  4. 4.Department of BiostatisticsUniversity of CopenhagenCopenhagenDenmark
  5. 5.Conservatoire National des Arts et MétiersParisFrance

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