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

被引:0
|
作者
Arthur Allignol
Jan Beyersmann
Thomas Gerds
Aurélien Latouche
机构
[1] University of Freiburg,Freiburg Centre for Data Analysis and Modelling
[2] University of Ulm,Institute of Statistics
[3] University Medical Center Freiburg,Institute of Medical Biometry and Medical Informatics
[4] University of Copenhagen,Department of Biostatistics
[5] Conservatoire National des Arts et Métiers,undefined
来源
Lifetime Data Analysis | 2014年 / 20卷
关键词
Left-truncation; Bivariate survival; Nosocomial infection; Markov assumption; Multi-state model;
D O I
暂无
中图分类号
学科分类号
摘要
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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收藏
页码:495 / 513
页数:18
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