报告题目：Additive hazards regression for misclassified current status data
报 告 人：李树威 副教授 广州大学
报告时间：2021年3月22日 14:30-15:30
报告地点：腾讯会议ID：576 793 038
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https://meeting.tencent.com/s/W4O1WAWfzeyF
校内联系人：程建华 chengjh@jlu.edu.cn
报告摘要：
We discuss regression analysis of current status data with the additive hazards model when the failure status may suffer misclassification. Such data occur commonly in many scientific fields involving the diagnosis test with imperfect sensitivity and specificity. In particular, we consider the situation where the sensitivity and specificity are known and propose a nonparametric maximum likelihood approach. For the implementation of the method, a novel EM algorithm is developed, and the asymptotic properties of the resulting estimators are established. Furthermore, the estimated regression parameters are shown to be semiparametrically efficient. We demonstrate the empirical performance of the proposed methodology in a simulation study and show its substantial advantages over the naive method. Also an application to a motivated study on chlamydia is provided.
报告人简介：
李树威，广州大学统计系副教授，研究生导师，研究领域为生物统计、生存分析、纵向数据等。目前已发表10余篇高水平科研论文，主持国家自然科学基金1项。
