ORCID
- Małgorzata Wojtyś: 0000-0002-6598-9572
- Yinghui Wei: 0000-0002-7873-0009
Abstract
Non-terminal and terminal events in semi-competing risks data are typically associated and may be influenced by covariates. We employed regression modeling for semi-competing risks data under a copula-based framework to evaluate the effects of covariates on the two events and the association between them. Due to the complexity of the copula structure, we propose a new method that integrates a novel two-step algorithm with the Bound Optimization by Quadratic Approximation (BOBYQA) method. This approach effectively mitigates the influence of initial values and demonstrates greater robustness. The simulations validate the performance of the proposed method. We further applied our proposed method to the Amsterdam Cohort Study (ACS) real data, where some improvements could be found.
Publication Date
2025-05-13
Publication Title
Entropy
Volume
27
Issue
5
ISSN
1099-4300
Keywords
Amsterdam Cohort Study, BOBYQA, copula, right censoring, semi-competing risks
First Page
521
Last Page
521
Recommended Citation
Zhang, Q., Duan, B., Wojtyś, M., & Wei, Y. (2025) 'Two-Step Estimation Procedure for Parametric Copula-Based Regression Models for Semi-Competing Risks Data', Entropy, 27(5), pp. 521-521. Available at: 10.3390/e27050521
