网站首页  学院概况  师资队伍  本科生教育  研究生教育  科学研究  党委专栏  学生活动 
当前位置: 网站首页 > 学术讲座 > 正文

Causal Inference with Measurement Error in Outcomes

发布时间:2018年07月08日 10:34   浏览次数:
报告人 Grace Y. Yi 年月 2018年7月
9日

报告题目:Causal Inference with Measurement Error in Outcomes

报告人:Grace Y. Yi

报告人单位:University of Waterloo

报告时间:79日(周一)上午10:30-11:30

报告地点:数学学院西303报告厅 

邀请人:周杰

 

Abstract:

 

Inverse probability weighting (IPW) estimation has been popularly used to

consistently estimate the average treatment effect (ATE). Its validity, however, is

challenged by the presence of error-prone variables. In application, measurement

error is ubiquitously present in data collection due to various reasons. Naively

ignoring measurement error effects usually yields biased inference results. In

this talk, I will discuss the IPW estimation with mismeasured outcome variables.

The impact of measurement error for both continuous and discrete outcome

variables will be examined. I will describe estimation procedures with the outcome

misclassification effects accommodated. Consistency and efficiency will be investigated.

Numerical studies will be reported to assess the performance of the proposed methods.

 

 

关闭

Copyright © 2018四川大学数学学院版权所有
 地址:成都市一环路南一段24号
电话:028-85412720