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科学研究
RESEARCH
Subgroup analysis of linear models with measurement error
时间  Datetime
2020-08-19 14:30 — 15:30
地点  Venue
Zoom APP(2)()
报告人  Speaker
秦国友
单位  Affiliation
复旦大学
邀请人  Host
统计系
备注  remarks
Zoom 会议号:663 173 51260 会议密码: 753637
报告摘要  Abstract

报告摘要: Heterogeneity exists in population and people may benefit differently from the same treatment or services. Correctly identifying different subgroups according to their outcome such as treatment responses plays an important role in providing data based evidence for intervention in practice. With few discussions on subgroup analysis in regression with measurement error, we propose a new estimation method of subgroup analysis with the existence of measurement error under the linear regression model. First, we develop an objective function based on the unbiased estimating equations with two replicate measurements and the concave penalty with the pairwise differences of coefficients. The proposed method can identify the subgroups and estimate coefficients simultaneously with the consideration of measurement error. Second, we derive the algorithm with concave penalties based on the alternating direction method of multipliers and demonstrate its convergence. Third, we prove that the proposed estimates hold the consistency and asymptotic normality. The performance of the proposed method and its asymptotic property are evaluated by simulations. Finally, we apply our method to the data from the Lifestyle Education for Activity and Nutrition study and identify two subgroups with one group having significant treatment effect.


报告人简介:秦国友,教授,博士生导师,复旦大学公共卫生学院生物统计学教研室主任。主要研究兴趣包括纵向数据分析,复杂数据分析, 部分线性模型,因果推断等统计方法研究以及现代统计方法在医学和公共卫生中的应用。主持三项国家自然科学基金项目,在BMJ, Biometrics、Biostatistics以及Statistics in medicine等国际权威医学和生物统计期刊上发表SCI学术论文70余篇,纵向数据分析相关研究工作获得2014年度教育部高等学校科学研究优秀成果奖二等奖。担任中华预防医学会生物统计分会第一届青年委员会主任委员,中国卫生信息学会健康统计专业委员会第四届委员会常务委员,中华预防医学会健康保险分会常务委员以及<<中国卫生统计>>编委。