Li Zhi-wen, Zhang Le, Liu Jian-meng, Ren Ai-guo
Institute of Reproductive and Child Health, Peking University Health Science Center, Beijing 100191, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2009 May;30(5):514-7.
In this article, we presented the rationale and calculation procedures of the propensity score matching (PSM), and its application in the designing stage of an epidemiological study. Based on existing observational data, PSM can be used to select one or more comparable controls for each subject in 'treatment' group according to the propensity scores estimated by 'treatment' variable and main covariates. The results of an example analysis showed that the bias for main confounders between the treated and control samples declined more than 55% after PMS.
PSM can reduce most of the confounding bias of the observational study, and can obtain approximate study effect to the randomized controlled trials when used in the designing of the epidemiological study.
在本文中,我们介绍了倾向得分匹配(PSM)的基本原理和计算程序,及其在流行病学研究设计阶段的应用。基于现有的观察数据,PSM可根据“治疗”变量和主要协变量估计的倾向得分,为“治疗”组中的每个受试者选择一个或多个可比对照。实例分析结果表明,倾向得分匹配后,治疗组与对照组样本之间主要混杂因素的偏差下降了55%以上。
PSM可减少观察性研究中的大部分混杂偏倚,在流行病学研究设计中使用时,可获得与随机对照试验近似的研究效果。