{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:16:19Z","timestamp":1760058979596,"version":"build-2065373602"},"reference-count":37,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2025,5,13]],"date-time":"2025-05-13T00:00:00Z","timestamp":1747094400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the China Scholarship Council (CSC)","award":["CSC-503854","CSC-557660"],"award-info":[{"award-number":["CSC-503854","CSC-557660"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/e27050521","type":"journal-article","created":{"date-parts":[[2025,5,13]],"date-time":"2025-05-13T11:31:49Z","timestamp":1747135909000},"page":"521","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Two-Step Estimation Procedure for Parametric Copula-Based Regression Models for Semi-Competing Risks Data"],"prefix":"10.3390","volume":"27","author":[{"given":"Qingmin","family":"Zhang","sequence":"first","affiliation":[{"name":"Yunnan Key Laboratory of Statistical Modeling and Data Analysis, Yunnan University, Kunming 650500, China"}]},{"given":"Bowen","family":"Duan","sequence":"additional","affiliation":[{"name":"Yunnan Key Laboratory of Statistical Modeling and Data Analysis, Yunnan University, Kunming 650500, China"}]},{"given":"Ma\u0142gorzata","family":"Wojty\u015b","sequence":"additional","affiliation":[{"name":"Centre for Mathematical Sciences, School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth PL4 8AA, UK"}]},{"given":"Yinghui","family":"Wei","sequence":"additional","affiliation":[{"name":"Centre for Mathematical Sciences, School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth PL4 8AA, UK"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"907","DOI":"10.1093\/biomet\/88.4.907","article-title":"On semi-competing risks data","volume":"88","author":"Fine","year":"2001","journal-title":"Biometrika"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1111\/j.1541-0420.2009.01340.x","article-title":"Statistical analysis of illness\u2013death processes and semicompeting risks data","volume":"66","author":"Xu","year":"2010","journal-title":"Biometrics"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1384","DOI":"10.2307\/2533269","article-title":"Inferences on the association parameter in copula models for bivariate survival data","volume":"51","author":"Shih","year":"1995","journal-title":"Biometrics"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Ramadan, D.A., Hasaballah, M.M., Abd-Elwaha, N.K., Alshangiti, A.M., Kamel, M.I., Balogun, O.S., and El-Awady, M.M. 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