Kaplan-Meier estimator in competing risk contexts

dc.contributor.author	Martínez-Camblor P.
dc.date.accessioned	2020-09-02T22:22:28Z
dc.date.available	2020-09-02T22:22:28Z
dc.date.issued	2016
dc.identifier	10.15672/HJMS.20157111086
dc.identifier.citation	45, 4, 1161-1173
dc.identifier.issn	2651477X
dc.identifier.uri	https://hdl.handle.net/20.500.12728/5245
dc.description	Survival analysis has become in a common procedure in biomedical researches. Conventionally, the well-known nonparametric Kaplan-Meier (KM) estimator is used in order to approximate the real survivor curve. However, in competing risk contexts where more than one failure cause compete to occur and only one of them is of interest, the direct use of the Kaplan-Meier statistic does not perform correctly and, in order to obtain a good estimation, it must be adapted. In this work, via Monte Carlo simulations, the author explores the behavior of the Kaplan-Meier estimator in a competing risk context. In addition, differences between KM and multiple decrement methods are pointed out. Finally, a real-data problem is used in order to illustrate the situation. © 2016, Hacettepe University. All rights reserved.
dc.language.iso	en
dc.publisher	Hacettepe University
dc.subject	Competing risks
dc.subject	Kaplan-Meier estimator
dc.subject	Multiple decrement
dc.subject	Survival analysis
dc.title	Kaplan-Meier estimator in competing risk contexts
dc.type	Article

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