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A Joint Modeling Approach for Analyzing Marker Data in the Presence of a Terminal Event
奥门金沙:2020年09月14日 10:15 点击数:

报告人:周洁

报告地点:Tencent会议

报告奥门金沙:2020年09月17日星期四14:30-15:30

邀请人:郑术蓉

报告摘要:

In many medical studies, markers are contingent on recurrent events and the cumulative markers are usually of interest. However, the recurrent event process is often interrupted by a dependent terminal event, such as death. In this article, we propose a joint modeling approach for analyzing marker data with informative recurrent and terminal events.

This approach introduces a shared frailty to specify the explicit dependence structure among the markers, the recurrent and terminal events. Estimation procedures are developed for the model parameters and the degree of dependence, and the asymptotic properties of the proposed estimators are established. In addition, a prediction of the covariate-specific cumulative markers is provided. The finite sample performance of the proposed estimators is examined through simulation studies. An application to a medical cost study of chronic heart failure patients from the University of Virginia Health System is illustrated.

会议ID:354 304 035

主讲人概况:

周洁副教授就职于首都师范大学数学科学学院,主要从事生存分析、复发事件与纵向数据的研究,在JASA,Biometrics, Statistica Sinica等国内外重要统计学杂志上发表SCI论文20余篇,主持多项北京市科研项目以及2项国家自然科学基金项目。

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