Goodness-of-fit diagnostics for the propensity score model when estimating treatment effects using covariate adjustment with the propensity score
Goodness-of-fit diagnostics for the propensity score model when estimating treatment effects using covariate adjustment with the propensity score
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DOI：
10.1002/pds.1673
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发表时间：
2008-12-01
影响因子：
2.6
通讯作者：
Austin, Peter C.
中科院分区：
文献类型：
--
作者：
Austin, Peter C.
倾向评分定义为受试者选择治疗的概率，以观察到的基线协变量为条件。在倾向评分的条件下，治疗和未治疗受试者的观察到的基线协变量分布相似。在医学文献中，有三种常用的倾向评分方法：倾向评分的分层（亚分类），倾向评分的匹配，以及使用倾向评分的协变量调整。已经开发了方法来评估倾向评分模型在倾向评分和倾向评分匹配分层的背景下的充分性。然而，尚未开发出使用倾向评分进行协变量调整的可比方法。仅当在倾向评分的条件下，接受治疗和未接受治疗的受试者具有相似的基线协变量分布时，使用倾向评分方法进行的治疗效应推断才有效。我们开发了定量和定性方法来评估治疗和未治疗受试者之间基线协变量的平衡。定量方法采用加权条件标准差法。这是治疗和未治疗受试者之间协变量均值的条件差异，以合并标准差为单位，在倾向评分分布上积分。定性方法采用分位数回归模型，以确定在倾向评分的条件下，接受治疗和未接受治疗的受试者是否具有相似的连续协变量分布。我们使用诊断为心脏病发作（急性心肌梗死）的出院患者的大型数据集来说明我们的方法。暴露为出院时接受β受体阻滞剂处方。版权所有（C）2008约翰威利父子有限公司
The propensity score is defined to be a subject's probability of treatment selection, conditional on observed baseline covariates. Conditional on the propensity score, treated and untreated subjects have similar distributions of observed baseline covariates. In the medical literature, there are three commonly employed propensity-score methods: stratification (sub-classification) on the propensity score, matching on the propensity score, and covariate adjustment using the propensity score. Methods have been developed to assess the adequacy of the propensity score model in the context of stratification on the propensity score and propensity-score matching. However, no comparable methods have been developed for covariate adjustment using the propensity score. Inferences about treatment effect made using propensity-score methods are only valid if, conditional on the propensity score, treated and untreated subjects have similar distributions of baseline covariates. We develop both quantitative and qualitative methods to assess the balance in baseline covariates between treated and untreated subjects. The quantitative method employs the weighted conditional standardized difference. This is the conditional difference in the mean of a covariate between treated and untreated subjects, in units of the pooled standard deviation, integrated over the distribution of the propensity score. The qualitative method employs quantile regression models to determine whether, conditional on the propensity score, treated and untreated subjects have similar distributions of continuous covariates. We illustrate our methods using a large dataset of patients discharged from hospital with a diagnosis of a heart attack (acute myocardial infarction). The exposure was receipt of a prescription for a beta-blocker at hospital discharge. Copyright (C) 2008 John Wiley & Sons, Ltd.