Methods for Constructing and Assessing Propensity Scores
Methods for Constructing and Assessing Propensity Scores
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DOI：
10.1111/1475-6773.12182
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发表时间：
2014-10-01
影响因子：
3.4
通讯作者：
Aldridge, Melissa D.
中科院分区：
文献类型：
--
作者：
Garrido, Melissa M.;Kelley, Amy S.;Aldridge, Melissa D.
目标.通过提供逐步指导和应用于经验数据集的Stata代码，对准备和执行倾向评分分析所涉及的步骤进行建模。给出了指南、Stata代码和经验示例，以说明（1）选择纳入倾向评分的变量的过程;（2）治疗组和对照组之间倾向评分的平衡;（3）倾向评分块内治疗组和对照组之间协变量的平衡;（4）匹配和加权策略的选择;（5）样本匹配或加权后协变量的平衡;（6）治疗效果估计的解释。实证应用。我们使用来自癌症患者姑息治疗（PC 4C）研究的数据，这是一项关于住院姑息治疗对患者健康结局和卫生服务使用的影响的多中心观察性研究，以说明倾向评分的发展和使用。倾向评分是解释治疗组和对照组之间观察到的差异的一种有用工具。在使用倾向评分来估计治疗效果之前，需要仔细测试倾向评分。
Objectives. To model the steps involved in preparing for and carrying out propensity score analyses by providing step-by-step guidance and Stata code applied to an empirical dataset.Study Design. Guidance, Stata code, and empirical examples are given to illustrate (1) the process of choosing variables to include in the propensity score; (2) balance of propensity score across treatment and comparison groups; (3) balance of covariates across treatment and comparison groups within blocks of the propensity score; (4) choice of matching and weighting strategies; (5) balance of covariates after matching or weighting the sample; and (6) interpretation of treatment effect estimates.Empirical Application. We use data from the Palliative Care for Cancer Patients (PC4C) study, a multisite observational study of the effect of inpatient palliative care on patient health outcomes and health services use, to illustrate the development and use of a propensity score.Conclusions. Propensity scores are one useful tool for accounting for observed differences between treated and comparison groups. Careful testing of propensity scores is required before using them to estimate treatment effects.