报 告 人:
中国科学院数学与系统科学研究院研究员、上海财经大学
报告题目:Semiparametric Estimation of Treatment Effect with Logistic Regression Model
时 间:
地 点:成功楼603
主 办:数学与计算机科学学院
报告摘要:
Treatment effect is an important index in comparing two-sample data in survival analysis, industry manufacture, clinical medicine and many other applications. In this paper, we propose a unified semiparametric approach to estimate different types of treatment effects under a case-control sampling plan with the logistic regression model assumption, which is equivalent to a two-sample density ratio model. For different treatment effects, we construct different estimating functions and the nuisance parameters in estimating functions are estimated firstly by the empirical likelihood method. Here, we allow that the functions are nonsmooth with respect to parameters. The confidence interval for the treatment effect based on the empirical likelihood ratio method is also presented. We prove that the estimator based on the estimating equation is consistent and asymptotically normal and the empirical log-likelihood ratio statistic has a limiting scaled chi-square distribution. Simulation studies are reported to assess the finite sample properties of the proposed estimator and the performance of the confidence interval. The proposed methods are applied to real data examples and some interesting results are presented.
专家简介:
周勇研究员主要从事统计学研究,在数量金融与风险管理、计量经济学、 生存分析和生物统计等方面做出突出贡献。曾主持与主要参加完成国家级和省部级项目7项,是国家973重大项目骨干成员(排名2)和863 重大项目主要成员。周勇研究员的研究成果曾发表在国际顶级统计杂志《Annals of Statistics》 (SCI 1区),《Journal of the American Statistical Association》(SCI 1区)和顶级计量经济学杂志《Journal of Econometrics》(SSCI 2区)等权威杂志上。论文被SCI引用212次,SCI 他引190次。