Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/142822
Title: Frailty modelling approaches for semi-competing risks data
Authors: Ha, Il Do
Xiang, Liming
Peng, Mengjiao
Jeong, Jong-Hyeon
Lee, Youngjo
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

Files in This Item:
File Description SizeFormat 
LIDA_2018_3rd_revision.pdf291.37 kBAdobe PDFView/Open

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.