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|Title:||Frailty modelling approaches for semi-competing risks data||Authors:||Ha, Il Do
|Keywords:||Science::Mathematics||Issue Date:||2020||Source:||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||Journal:||Lifetime data analysis||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.||URI:||https://hdl.handle.net/10356/142822||ISSN:||1380-7870||DOI:||10.1007/s10985-019-09464-2||Rights:||© 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.||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SPMS Journal Articles|
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