演講公告

東海大學統計學系學術演講20171121

公告時間:2017-11-21 09:51:18
公告單位:統計學系

 

 

東海大學統計學系學術演講

時 間:106年11 月21日(星期二下午14:10~15:00)

地 點:管理學院新大樓M146

主講人:黃名鉞 助研究員 (中研院統計研究所)

講 題:Sufficient Dimension Reduction in Causal Inference

Abstract

In medical and social studies, the main interest is to investigate the causal effect of

a treatment on an outcome variable. While the estimation of average treatment effects

usually involves multivariate confounders, dimension reduction become a useful approach

to reduce the curse of dimensionality and perform more stable estimation. In this talk, I

will discuss the Neyman-Rubin model and clarify the definition of a central subspace that

is relevant for the efficient estimation of average treatment effects. Under the ignorable

selection, we propose a joint cross-validation type criterion to simultaneously estimate the

structural dimensions, the basis matrices of the proposed central subspaces, and the optimal

bandwidths for estimating the conditional treatment effects. Related large sample properties

and finite sample performance will also be discussed.

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