讲座题目：Model-Assisted Regression Estimators for Longitudinal Data with Nonignorable Dropout
主 讲 人：威斯康辛大学麦迪逊分校邵军教授
讲座时间：2019年10月30日（周三）14:00-15:00
讲座地点：6号学院楼４楼402
主办单位：银河7163官网
摘 要：
Estimation with longitudinal data having nonignorable dropout is considered when the joint distribution of the study variable and covariate is nonparametric and the dropout propensity follows a parametric model. To deal with the identifiability problem caused by nonignorable dropout, we use an instrument which is a covariate unrelated to the dropout propensity. We apply the generalized method of moments to estimate the parameters in the dropout propensity model based on some estimating equations constructed using the instrument. Population means and other parameters in the nonparametric distribution of the study variable can be estimated based on inverse propensity weighting with weights constructed after addressing the nonignorable dropout. To improve efficiency, we derive a model-assisted regression estimator making use of extra information provided by the covariates and previously observed study variables in the longitudinal setting. The model-assisted regression estimator is protected from model mis-specification, and is shown to be asymptotically normal and more efficient than the estimator based on inverse propensity weighting when the working models are correct or nearly correct and some other conditions are satisfied. The finite-sample performance of the estimators is studied through simulation, and an application to the HIV-CD4 data set is also presented as illustration.
主讲人简介：
邵军，美国威斯康辛-麦迪逊大学统计系教授，1996年获美国数理统计学会Fellow，1999年获美国统计学会Fellow，多次获得美国自然科学基金，曾担任美国威斯康星-麦迪逊分校统计系系主任（2005-2009）、泛华统计学会会长（2007），现兼任美国国家统计局高级研究员，并任美国多家制药厂的统计顾问，现为华东师范大学特聘教授。邵教授曾任JASA、Statistica Sinica副主编，Journal of Multivariate Analysis和Sankhya联合主编，现任Journal of Nonparametric Statistics 主编，Journal of System Science and Complexity联合主编，2017年联合创立Statistical Theory and Related Fields 并担任总编辑。邵教授的6本统计学专著和课本之一的《数理统计》已成为数理统计理论名著，并成为北美和中国多个大学的统计学研究生教材。自1987年以来邵教授共发表学术论文180余篇，在重抽样技术、变量选择、生物统计和缺失数据的统计处理等方面做了大量的开创性工作。
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