• 演讲人： 童铁军（香港浸会大学数学系）
• 时间：2019年11月11日 周一下午3：00-4：00
• 地点：紫金港校区行政楼1417报告厅
• 主办单位：浙江大学数据科学研究中心

摘要：

Evidence-based medicine is attracting increasing attention to improve decision making in medical practice via integrating evidence from well designed and conducted clinical research. Meta-analysis is a statistical technique widely used in evidence-based medicine for analytically combining the findings from independent clinical trials to provide an overall estimation of a treatment effectiveness. The sample mean and standard deviation are two commonly used statistics in meta-analysis but some trials use the median, the minimum and maximum values, or sometimes the first and third quartiles to report the results. Thus, to pool results in a consistent format, researchers need to transform those information back to the sample mean and standard deviation. In this talk, I will introduce our recent advances in the optimal estimation of the sample mean and standard deviation for meta-analysis from both theoretical and empirical perspectives. Specifically, we solve the problems by incorporating the sample size in a smoothly changing weight in the estimators to reach the optimal estimation. Our proposed estimators not only improve the existing ones significantly but also share the same virtue of the simplicity. The real data application indicates that our proposed estimators are capable to serve as ‘‘rules of thumb’’ and will be widely applied in evidence-based medicine.

欢迎广大师生踊跃参加!

联系人：蒋杭进（jianghj@zju.edu.cn）

             浙江大学数据科学研究中心

报告人简介：

童铁军，香港浸会大学副教授，国际统计协会当选会员，主要科研方向为高维数据分析，Meta分析和循证医学。于2005年在美国加州大学圣巴巴拉分校获得统计学博士学位，2005-2007年在美国耶鲁大学从事生物统计博士后研究，2007-2011年在科罗拉多大学博尔德分校担任助理教授，目前在香港浸会大学数学系担任终身副教授，博士生导师。已在国际知名的学术期刊Journal of the American Statistical Association，Biometrika，Statistical Science，Journal of Machine Learning Research等发表学术论文60余篇，单篇论文最高引用800余次。曾主持香港研究資助局项目，香港卫生署健康与医学研究基金项目，国家自然科学基金面上项目等校内外科研项目多项。