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A competing risks approach for nonparametric estimation of transition probabilities in a non-Markov illness-death model
Authors:Arthur Allignol  Jan Beyersmann  Thomas Gerds  Aurélien Latouche
Institution:1. Freiburg Centre for Data Analysis and Modelling, University of Freiburg, Freiburg, Germany
3. Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Freiburg, Germany
2. Institute of Statistics, University of Ulm, Ulm, Germany
4. Department of Biostatistics, University of Copenhagen, Copenhagen, Denmark
5. Conservatoire National des Arts et Métiers, Paris, France
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.
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