Estimation of the average causal effect vis multiple propensity score stratification
Estimation of the average causal effect vis multiple propensity score stratification
复制标题
平均因果效应与多重倾向得分分层的估计
DOI：
10.1080/03610918.2016.1208230
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Hattori S
中科院分区：
文献类型：
--
作者：
Nomura T;Hattori S
假设我们有兴趣从观察性研究中估计总体平均值的平均因果效应(ACE)。由于简单易行，倾向评分分层法(PS)被广泛用于调整ACE估计中混杂因素的影响。PS分层估计的适当性取决于PS的正确说明。我们提出了一种基于分层的多PS模型估计器，该估计器采用聚类技术来代替模型选择。如果其中一个是正确的，则所提出的估计器消除了偏差，因此比标准的PS分层更稳健。
Suppose we are interested in estimating the average causal effect (ACE) for the population mean from observational study. Because of simplicity and ease of interpretation, stratification by a propensity score (PS) is widely used to adjust for influence of confounding factors in estimation of the ACE. Appropriateness of the estimation by the PS stratification relies on correct specification of the PS. We propose an estimator based on stratification with multiple PS models by clustering techniques instead of model selection. If one of them correctly specifies, the proposed estimator removes bias and thus is more robust than the standard PS stratification.