典型文献
Estimating Survival Treatment Effects with Covariate Adjustment Using Propensity Score
文献摘要：
Propensity score is widely used to estimate treatment effects in observational studies.The covariate adjustment using propensity score is the most straightforward method in the literature of causal inference.In this article,we estimate the survival treatment effect with covariate adjustment using propensity score in the semiparametric accelerated failure time model.We establish the asymp-totic properties of the proposed estimator by simultaneous estimating equations.We conduct simulation studies to evaluate the finite sample performance of the proposed method.A real data set from the German Breast Cancer Study Group is analyzed to illustrate the proposed method.
文献关键词：
中图分类号：
作者姓名：
Yong Xiu CAO;Xin Cheng ZHANG;Ji Chang YU
作者机构：
School of Statistics and Mathematics,Zhongnan University of Economics and Law,Wuhan 430073,P.R.China
文献出处：
引用格式：
[1]Yong Xiu CAO;Xin Cheng ZHANG;Ji Chang YU-.Estimating Survival Treatment Effects with Covariate Adjustment Using Propensity Score)[J].数学学报（英文版）,2022(11):2057-2068
A类：
Covariate,semiparametric,totic
B类：
Estimating,Survival,Treatment,Effects,Adjustment,Using,Propensity,Score,score,widely,used,estimate,treatment,effects,observational,studies,covariate,adjustment,using,propensity,most,straightforward,method,literature,causal,inference,In,this,article,we,survival,accelerated,failure,model,We,establish,asymp,properties,proposed,estimator,by,simultaneous,estimating,equations,conduct,simulation,evaluate,finite,sample,performance,real,data,set,from,German,Breast,Cancer,Study,Group,analyzed,illustrate
AB值：
0.638029
相似文献
机标中图分类号，由域田数据科技根据网络公开资料自动分析生成，仅供学习研究参考。
