【主题】A Versatile Estimation Procedure without Estimating the Nonignorable Missingness Mechanism
【报告人】Ma Yanyuan , 教授
美国宾州州立大学统计系
【时间】 2019年6月12日（星期三）14:00-15:00
【地点】上海财经大学统计与管理学院大楼1208会议室
【摘要】We consider the estimation problem in a regression setting where the outcome variable is subject to nonignorable missingness and identifiability is ensured by the shadow variable approach. We propose a versatile estimation procedure where modeling of missingness mechanism is completely bypassed. We show that our estimator is easy to implement and we derive the asymptotic theory of the proposed estimator. We also investigate some alternative estimators under different scenarios. Comprehensive simulation studies are conducted to demonstrate the finite sample performance of the method. We apply the estimator to a children's mental health study to illustrate its usefulness.
【嘉宾简介】Dr. Ma is Professor in Statistics in the department of statistics in the Pennsylvania State University, U.S. Her research interests include Measurement error models, Dimension reduction, Mixed sample problems, Latent variable models, Selection bias and Skew-elliptical distributions, Semiparametrics.
【主持人】冯兴东
