★演講公告：
★講題：Causal Mediation Analysis: A Summary-Data Mendelian Randomization Approach
★摘要：Summary-data Mendelian randomization (MR) has emerged as a powerful approach for causal mediation analysis, providing an alternative to traditional methods. Two MR-based frameworks—analogous to the difference and product methods—are typically implemented using inverse-variance weighted estimation (MR-IVW). Despite their popularity, these existing approaches often suffer from limited statistical efficiency, lack of robustness, and insufficiently rigorous inference procedures.
In this talk, I will present our recent developments on improved MR-based mediation frameworks using summary-level data, commonly available from genome-wide association studies (GWAS). Specifically, we propose novel variance estimators for mediation effects, establish formal inference procedures, and introduce robust strategies to address pleiotropy. These methodological advances enhance the reliability and applicability of MR mediation analysis in practice.
★講者介紹：林書勤(國立臺灣大學統計與數據科學研究所助理教授)
★日期：2025年10月16日（四）
★時間：中午12點開始入場、12:20PM-13:30PM演講
★地點：公共衛生學院1樓全球廳
★報名網址：https://reurl.cc/vL2eQ1
★截止時間：10月13日（一）中午12點前完成報名，人數上限50人，額滿截止。
★本活動中午提供簡易輕食，並請自行攜帶水杯
主辦單位：國立臺灣大學健康資料研究中心
協辦單位：國立臺灣大學公共衛生學院、健康數據拓析統計研究所