题目：Semiparametric regression analysis of family history data in an Alzheimer’s disease study

报告人：梁宝生（北京大学医学部）

Abstract : Large cohort studies are commonly launched to study risk of genetic variants or other risk factors on age at onset (AAO) of a chronic disorder. In these studies, family history data including AAO of disease in family members are collected to provide additional information and can be used to improve efficiency. Statistical analysis of these data is challenging due to missing genotypes in family members and the heterogeneous dependence attributed to both shared genetic background and shared environmental factors. In this paper, we propose a class of semiparametric transformation models with multi-level random effects to tackle these challenges. The proposed models include both proportional hazards model and proportional odds model as special cases. The multi-level random effects contain individual-speci?c random effects including kinship correlation structure dependent on the family pedigree, and a shared random effect to account for unobserved environment exposure. We use nonparametric maximum likelihood approach for inference and propose an expectation-maximization algorithm for computation in the presence of missing genotypes among family members. The obtained estimators are shown to be consistent, asymptotically normal, and semiparametrically effcient. Finally, the proposed method is applied to study genetic risks in an Alzheimer’s disease study.

简介：梁宝生，北京大学公共卫生学院生物统计系助理教授。于2016年博士毕业于北京师范大学概率论与数理统计专业，曾以联合培养博士生身份在美国北卡罗来纳大学教堂山分校学习生物统计学，后前往美国纽约哥伦比亚大学生物统计系工作和学习，博士毕业后，前往香港大学统计及精算系做博士后。研究方向为生存分析、不完全观测数据分析和统计学习算法等，在震后PTSD、帕金森疾病、阿尔兹海默病和肺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等期刊发表SCI论文13篇, 参与完成译著1部。 主持省部级以上自然科学基金2项（青年科学基金），以骨干成员参加国自然面上项目2项。

时间：2020年10月8日（周四）下午20:30-21:30

地点：线上腾讯会议（会议号：66676005472）

联系人：周洁

欢迎全体师生积极参加！