Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group
Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group
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DOI：
10.1002/(sici)1097-0258(19981015)17:19
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发表时间：
1998-10-15
影响因子：
2
通讯作者：
D'Agostino, RB
中科院分区：
文献类型：
--
作者：
D'Agostino, RB
在观察性研究中，研究者无法控制治疗分配。给药组和非给药组（即对照组）在其观察到的协变量上可能存在较大差异，这些差异可能导致给药效应的偏倚估计。甚至传统的协方差分析调整可能不足以消除这种偏差。倾向评分定义为给定协变量的接受治疗的条件概率，可用于平衡两组中的协变量，从而降低偏倚。为了估计倾向评分，必须根据观察到的协变量对治疗指标变量的分布进行建模。一旦估计，倾向评分可用于通过匹配、分层（子分类）、回归调整或所有三者的某种组合来减少偏倚。在本教程中，我们将讨论使用倾向评分方法减少偏倚，参考文献，并通过应用示例说明其用途。(C)John Wiley & Sons，Ltd.
In observational studies, investigators have no control over the treatment assignment. The treated and non-treated (that is, control) groups may have large differences on their observed covariates, and these differences can lead to biased estimates of treatment effects. Even traditional covariance analysis adjustments may be inadequate to eliminate this bias. The propensity score, defined as the conditional probability of being treated given the covariates, can be used to balance the covariates in the two groups, and therefore reduce this bias. In order to estimate the propensity score, one must model the distribution of the treatment indicator variable given the observed covariates. Once estimated the propensity score can be used to reduce bias through matching, stratification (subclassification), regression adjustment, or some combination of ail three. In this tutorial we discuss the uses of propensity score methods for bias reduction, give references to the literature and illustrate the uses through applied examples. (C) 1998 John Wiley & Sons, Ltd.