A New Joint Modeling Approach for Recurrent Event Data with Informative Terminal Event

发布时间：2023-02-16 作者：浏览次数：

Speaker:	周洁	DateTime:	2月19日（星期日）下午4：00-5：00
Brief Introduction to Speaker: 周洁，首都师范大学副教授，研究方向包括：生存分析，纵向数据分析，深度学习等领域；在Journal of the American Statistical Association，Biometrics，Statistica Sinica等期刊上发表论文20余篇；主持国家自然科学基金3项。		Place:	6号楼二楼报告厅
Abstract:In this article, we propose a new joint gamma frailty modeling approach for recurrent event data with informative terminal event by adopting a new type of double exponential Cox model to the terminal event. The proposed model overcomes the drawback that the marginal effects of covariates die out over time in gamma frailty Cox models. A sieve maximum likelihood approach is carried out for parameter estimation, and the Bernstein polynomials are employed to approximate the non-decreasing cumulative baseline functions. The EM algorithm is utilized for optimization. Asymptotic properties of the estimators are provided. Simulation studies are conducted to evaluate the finite sample behavior of the proposed estimators. A real dataset of readmissions of patients diagnosed with colorectal cancer is analyzed for illustration.