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学术报告: Estimating causal effects arising from a treatment sequence

发布时间:2019年01月14日 浏览次数:发布者:mathky

报告人:王小芹副教授 

      Department of Electrical Engineering, Mathematics and Sciences

Faculty of Engineering and Sustainable Development

University of Gävle

题目: Estimating causal effects arising from a treatment sequence

时间:2019年01月17日上午09:00

地点:海韵实验楼108

摘要: In economic and medical practices, a sequence of treatments are assigned to influence an outcome of interest that occurs after the last treatment. Between treatments, there exist time-dependent covariates that may be influenced by the earlier treatments and at the same time confounders of the subsequent treatments. The causal effects of interest are the net effects of individual treatments and the causal effect of a posited treatment regime on the outcome after the last treatment. In this seminar, we will first review the well-known difficulties of estimating these causal effects and then introduce a method of estimating these causal effects that can avoid the known difficulties.

Main references:

(1)   WANG, X. and YIN, L. (2015). Identifying and estimating net effects of treatments in sequential causal inference. Electron. J. Stat. 9 1608–1643. MR3379004

(2)   Wang, X. and Yin, L. (2019) new g-formula for the sequential causal effect and blip effect of treatment in sequential causal inference. To appear in Annals of Statistics.

报告人简介:

EDUCATION: Xiamen University, Bachelor Degree of Science, 1982-07, Mathematics 

Xiamen University, Master Degree of Science, 1985-07, Mathematics

Uppsala University, Degree of Doctor of Philosophy, 1990-05, Mathematics

PREVIOUS AND CURRENT POSITIONS:

Lecturer (universitetslektor) ,Department of Mathematics, Uppsala University,1990. 7 – 1994.6

Senior Lecturer,  Associate Professor, statistics,  University of Gävle,  1994 07

Researcher,     Department of Medical Epidemiology and Biostatistics,   Karolinska Institute 1998 01--1998 07

联系人:黄荣坦副教授

 

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