时间地点

中国矿业大学（北京）逸夫楼1537

2023年9月26日周二下午  14：00—15：00

报告题目

Title

Variable selection for mixed panel count data under the proportional mean model

摘要

Abstract

Mixed panel count data have attracted increasing attention in medical research based on event history studies. When such data arise, one either observes the number of event occurrences or only knows whether the event has happened or not over an observation period. In this paper, we discuss variable selection in event history studies given such complex data, for which there does not seem to exist an established procedure. For the problem, we propose a penalized likelihood variable selection procedure and for the implementation, an EM algorithm is developed with the use of the coordinate descent algorithm in the M-step.  Furthermore, the oracle property of the proposed method is established, and a simulation study is performed and indicates that the proposed method works well in practical scenarios.  Finally, the method is applied to identify the risk factors associated with medical non-adherence arising from the Sequenced Treatment Alternatives to Relieve Depression Study. This is a collaborative work with Dr. Lei Ge, Dr. Tao Hu, Dr. Jianguo Sun, Dr. Shishun Zhao, and Dr. Yang Li.

个人简介

Short Biography

梁宝生，北京大学公共卫生学院生物统计系，副研究员，博士生导师。2016年博士毕业于北京师范大学概率论与数理统计专业，2013至2016年博士在读期间先后以联合培养博士生和助研身份分别在美国北卡罗来纳大学教堂山分校生物统计系和美国纽约哥伦比亚大学生物统计系进行访问交流；2018年于香港大学统计及精算系博士后出站，并就职于北京大学医学部工作至今。感兴趣的研究领域为生存分析、非参数和半参数统计学以及统计学习等，在震后PTSD、帕金森疾病、阿尔兹海默病、肺癌、宫颈癌和乳腺癌等疾病的临床复杂数据的建模方法等方面开展了系列研究。在Biometrika、Statistica Sinica等国内外期刊发表论文30余篇, 合作完成译著1部，参与编写教材2部。主持国家自然科学基金青年项目1项，主持北京市自然科学基金1项，以骨干成员参加国自然面上项目2项，百度基金1项。