ORCID
- Wei, Yinghui: 0000-0002-7873-0009
- Wojtys, Malgorzata: 0000-0002-6598-9572
Abstract
Time-to-event semi-competing risk endpoints may be correlated when both events occur on the same individual. These events and the association between them may also be influenced by individual characteristics. In this article, we propose copula survival models to estimate hazard ratios of covariates on the non-terminal and terminal events, along with the effects of covariates on the association between the two events. We use the Normal, Clayton, Frank and Gumbel copulas to provide a variety of association structures between the non-terminal and terminal events. We apply the proposed methods to model semi-competing risks of graft failure and death for kidney transplant patients. We find that copula survival models perform better than the Cox proportional hazards model when estimating the non-terminal event hazard ratio of covariates. We also find that the inclusion of covariates in the association parameter of the copula models improves the estimation of the hazard ratios.
DOI
10.1177/09622802231188516
Publication Date
2023-08-09
Publication Title
Statistical Methods in Medical Research
ISSN
0962-2802
Embargo Period
2023-08-15
Organisational Unit
School of Engineering, Computing and Mathematics
Recommended Citation
Wei, Y., Wojtys, M., Sorrell, L., & Rowe, P. (2023) 'Bivariate copula regression models for semi-competing risks', Statistical Methods in Medical Research, . Available at: https://doi.org/10.1177/09622802231188516
