Frailty modelling approaches for semi-competing risks data

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 e...

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Main Authors: Ha, Il Do, Xiang, Liming, Peng, Mengjiao, Jeong, Jong-Hyeon, Lee, Youngjo
Other Authors: School of Physical and Mathematical Sciences
Format: Article
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/142822
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1428222023-02-28T19:41:00Z Frailty modelling approaches for semi-competing risks data Ha, Il Do Xiang, Liming Peng, Mengjiao Jeong, Jong-Hyeon Lee, Youngjo School of Physical and Mathematical Sciences Science::Mathematics Frailty Models Hierarchical Likelihood 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. MOE (Min. of Education, S’pore) Accepted version 2020-07-03T02:25:42Z 2020-07-03T02:25:42Z 2020 Journal Article Ha, I. D., Xiang, L., Peng, M., Jeong, J.-H., & Lee, Y. (2020). Frailty modelling approaches for semi-competing risks data. Lifetime data analysis, 26, 109–133. doi:10.1007/s10985-019-09464-2 1380-7870 https://hdl.handle.net/10356/142822 10.1007/s10985-019-09464-2 30734137 2-s2.0-85061176529 26 109 133 en Lifetime data analysis © 2019 Springer Science+Business Media. This is a post-peer-review, pre-copyedit version of an article published in Lifetime data analysis. The final authenticated version is available online at: http://dx.doi.org/10.1007/s10985-019-09464-2. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Science::Mathematics
Frailty Models
Hierarchical Likelihood
spellingShingle Science::Mathematics
Frailty Models
Hierarchical Likelihood
Ha, Il Do
Xiang, Liming
Peng, Mengjiao
Jeong, Jong-Hyeon
Lee, Youngjo
Frailty modelling approaches for semi-competing risks data
description 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.
author2 School of Physical and Mathematical Sciences
author_facet School of Physical and Mathematical Sciences
Ha, Il Do
Xiang, Liming
Peng, Mengjiao
Jeong, Jong-Hyeon
Lee, Youngjo
format Article
author Ha, Il Do
Xiang, Liming
Peng, Mengjiao
Jeong, Jong-Hyeon
Lee, Youngjo
author_sort Ha, Il Do
title Frailty modelling approaches for semi-competing risks data
title_short Frailty modelling approaches for semi-competing risks data
title_full Frailty modelling approaches for semi-competing risks data
title_fullStr Frailty modelling approaches for semi-competing risks data
title_full_unstemmed Frailty modelling approaches for semi-competing risks data
title_sort frailty modelling approaches for semi-competing risks data
publishDate 2020
url https://hdl.handle.net/10356/142822
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