倾向得分匹配
观察研究
因果推理
数学
计量经济学
协变量
统计
混淆
因果模型
医学
因果分析
因果关系(物理学)
工具变量
作者
Paul R. Rosenbaum,Donald B. Rubin
出处
期刊:Biometrika
[Oxford University Press]
日期:1983-01-01
卷期号:70 (1): 41-55
被引量:23295
标识
DOI:10.1093/biomet/70.1.41
摘要
The propensity score is the conditional probability of assignment to a particular treatment given a vector of observed covariates. Both large and small sample theory show that adjustment for the scalar propensity score is sufficient to remove bias due to all observed covariates. Applications include: (i) matched sampling on the univariate propensity score, which is a generalization of discriminant matching, (ii) multivariate adjustment by subclassification on the propensity score where the same subclasses are used to estimate treatment effects for all outcome variables and in all subpopulations, and (iii) visual representation of multivariate covariance adjustment by a two- dimensional plot.
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