主讲人：张岳 博士

时间：2016年12月13日（周二）晚上18：30

地点：南开大学(津南校区)437必赢国际线路144会议室

主讲人简介：

    张岳，南开大学社会心理学系本科毕业，美国University of Cincinnati统计学博士。现任上海交通大学生命科学技术学院生物信息学与生物统计学系助理研究员，上海交通大学－Yale University联合生物统计中心助理研究员。攻读博士学位期间，曾在University of Cincinnati数学学院担任助教，并在Procter & Gamble，Cincinnati Children's Hospital Medical Center实习。博士期间主要研究方向为贝叶斯方法分析生存模型及其在医学研究中的应用。张岳博士曾与Cincinnati Children's Hospital Medical Center许多科室展开合作研究，例如内分泌、哮喘、影像、精神病等。就职上海交通大学之后，开始与上海市第一人民医院神经内科合作。张岳博士的另一个主要研究方向是数据中缺失值研究，并将相应方法应用到生活质量调查数据的缺失值分析中。

讲座摘要：Nonresponse is an important practical problem in epidemiological surveys and clinical trials. Common methods for dealing with missing data rely on untestable assumptions. In particular, non-ignorable modeling, which derives inference from the likelihood function based on a joint distribution of the variables and the missingness indicators, can be sensitive to misspecification of this distribution and may also have problems with identifying the parameters. Nonresponse two-phase sampling (NTS), which re-contacts and collects data from a subsample of the initial nonrespondents, has been used to reduce nonresponse bias. The additional data collected in phase II provides important information for identifying the parameters in the non-ignorable models. We propose a Bayesian selection model which utilizes the additional data from phase II and develop an efficient Markov chain Monte Carlo algorithm for the posterior computation. We illustrate the proposed model on simulation studies and a Quality of Life (QOL) dataset.