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A comparison of propensity score matching methods for reducing selection bias

机译:倾向得分匹配方法减少选择偏见的比较

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Propensity score matching (PSM) has become a popular approach for research studies when randomization is infeasible. However, there are significant differences in the effectiveness of selection bias reduction among the existing PSM methods and, therefore, it is challenging for researchers to select an appropriate matching method. This current study compares four commonly used PSM methods for reducing selection bias on observational data from which the treatment effects are intended to be assessed. The selection bias, standardized bias and percent bias reduction are evaluated for each of the PSM methods using empirical data drawn from the national Education Longitudinal Study of 2002. The results of the current study provide empirical evidence and helpful information for researchers to select effective PSM methods for their research studies.View full textDownload full textKeywordspropensity score matching, propensity score analysis, nearest neighbour matching, caliper matching, Mahalanobis metric matching, stratification, selection biasRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/1743727X.2011.552338
机译:当随机化不可行时,倾向得分匹配(PSM)已成为研究的一种流行方法。但是,在现有PSM方法之间,降低选择偏差的有效性存在显着差异,因此,对于研究人员而言,选择合适的匹配方法具有挑战性。这项当前的研究比较了四种常用的PSM方法,以减少观察数据的选择偏倚,据此可以评估治疗效果。使用2002年国家教育纵向研究得出的经验数据对每种PSM方法的选择偏倚,标准偏倚和减少百分比偏倚进行了评估。本研究的结果为研究人员选择有效的PSM方法提供了经验证据和有用的信息。查看全文下载全文关键词关键词倾向得分匹配,倾向得分分析,最近邻匹配,卡尺匹配,马氏度量匹配,分层,选择偏差相关var addthis_config = {ui_cobrand:“泰勒和弗朗西斯在线”,service_compact:“ citeulike, netvibes,推特,technorati,可口,linkedin,facebook,stumbleupon,digg,google,更多”,发布:“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/1743727X.2011.552338

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