一、主講人介紹： 

李剛教授是美國加州大學洛杉磯分校(UCLA)生物統計系和計算醫學系教授，Jonsson綜合癌癥中心生物統計部主任。他是國際數理統計學會(IMS)、美國統計學會(ASA)、英國皇家統計學會(RSS)和國際統計學會(ISI)會士。也是Electronic Journal Statistics期刊的主編(2022-2024)。此外，他還擔任泛華統計協會主席(2022-2024)。研究領域包括生存分析、縱向數據分析、高維數據分析、臨床試驗和大規模電子健康記錄(EHR)和生物銀行數據的高性能統計計算。李剛教授在這些領域做出了重大貢獻，并與人合著了三本研究專著。此外，他的研究成果已發表150多篇論文，其中許多論文發表在國際頂尖期刊上，如Annals of Statistics, Journal of the American Statistical Association, and Journal of the Royal Statistical Society-B等。他曾主持多項美國國立衛生研究院(NIH)和美國國家科學基金會(NSF)基金。

二、講座信息

Recent discoveries have emphasized the importance of within-subject (WS) visit-to-visit variability of longitudinal biomarkers as significant risk factors for health outcomes. This talk introduces a novel joint model that incorporates a longitudinal biomarker with heterogeneous WS variability and a competing risks time-to-event outcome. The proposed model provides a valuable framework for testing heterogeneity in WS variability, exploring the association between WS variability and survival outcomes, and enabling dynamic prediction of survival by considering both the individual mean and WS variability of the biomarker. We present an expectation-maximization algorithm for semiparametric maximum likelihood estimation, along with a profile-likelihood method for standard error estimation and inference. Moreover, we have developed efficient computational algorithms specifically tailored for analyzing biobank-scale data with tens of thousands of subjects. Through simulation results, we demonstrate the advantages of our method over traditional joint models. To illustrate the practical implications of our approach, we apply it to the Multi-Ethnic Study of Atherosclerosis (MESA) data, yielding intriguing findings. 

講座時間：2023年7月4日（星期二） 9:30-10:30

講座地點：數學院424會議室

歡迎大家積極參加！

三、主辦單位

數學科學學院

國際合作與交流處

2023年6月28日