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Erschienen in: Lifetime Data Analysis 1/2020

07.02.2019

Frailty modelling approaches for semi-competing risks data

verfasst von: Il Do Ha, Liming Xiang, Mengjiao Peng, Jong-Hyeon Jeong, Youngjo Lee

Erschienen in: Lifetime Data Analysis | Ausgabe 1/2020

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Abstract

In the semi-competing risks situation where only a terminal event censors a non-terminal event, observed event times can be correlated. Recently, frailty models with an arbitrary baseline hazard have been studied for the analysis of such semi-competing risks data. However, their maximum likelihood estimator can be substantially biased in the finite samples. In this paper, we propose effective modifications to reduce such bias using the hierarchical likelihood. We also investigate the relationship between marginal and hierarchical likelihood approaches. Simulation results are provided to validate performance of the proposed method. The proposed method is illustrated through analysis of semi-competing risks data from a breast cancer study.

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Metadaten
Titel
Frailty modelling approaches for semi-competing risks data
verfasst von
Il Do Ha
Liming Xiang
Mengjiao Peng
Jong-Hyeon Jeong
Youngjo Lee
Publikationsdatum
07.02.2019
Verlag
Springer US
Erschienen in
Lifetime Data Analysis / Ausgabe 1/2020
Print ISSN: 1380-7870
Elektronische ISSN: 1572-9249
DOI
https://doi.org/10.1007/s10985-019-09464-2

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