首页|Partial Least Squares Method for Treatment Effect in Observational Studies with Censored Outcomes
Partial Least Squares Method for Treatment Effect in Observational Studies with Censored Outcomes
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维普
To estimate the true treatment effect on a censored outcome in observational studies,potential confounding effect and complex heterogeneity in the treatment assignment have to be properly adjusted.In this article,we demonstrate that the partial least squares method could be a valuable tool in this regard.It is showed that the partial least squares method not only can adequately account for the heterogeneity in treatment assignment,but also be robust to treatment assignment model misspecifications.Numerical results show that the partial least squares estimator is more efficient and robust.A real data set is analyzed to illustrate the proposed method.
heterogeneityobservational studypartial least squarespropensity score
CAO Yongxiu、YU Jichang
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School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan 430073, Hubei, China
Supported by the National Natural Science Foundation of ChinaSupported by the National Natural Science Foundation of China
NETL
NSTL
万方数据
维普
