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...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/142822 |
| _version_ | 1826119802820755456 |
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| author | Ha, Il Do Xiang, Liming Peng, Mengjiao Jeong, Jong-Hyeon Lee, Youngjo |
| 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 |
| author_sort | Ha, Il Do |
| collection | NTU |
| 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. |
| first_indexed | 2024-10-01T05:06:05Z |
| format | Journal Article |
| id | ntu-10356/142822 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:06:05Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | ntu-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 |
| 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 |
| title | 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_short | Frailty modelling approaches for semi-competing risks data |
| title_sort | frailty modelling approaches for semi competing risks data |
| topic | Science::Mathematics Frailty Models Hierarchical Likelihood |
| url | https://hdl.handle.net/10356/142822 |
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