Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples.
Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples.
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DOI：
10.1002/sim.3697
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发表时间：
2009-11-10
影响因子：
2
通讯作者：
Austin, Peter C.
中科院分区：
文献类型：
--
作者：
Austin, Peter C.
关键词：
倾向评分是受试者的治疗概率，以观察到的基线协变量为条件。在真实倾向评分的条件下，治疗和未治疗受试者的观察基线协变量分布相似。倾向评分匹配是医学文献中使用倾向评分的常用方法。使用这种方法，形成具有相似倾向评分值的治疗和未治疗受试者的匹配集。仅当在匹配样本中，治疗和未治疗受试者的基线测量协变量分布相似时，使用倾向评分匹配进行的治疗效应推断才有效。在本文中，我们讨论了以下方法来评估是否已正确指定的倾向评分模型：比较平均值和基线特征的患病率使用标准化差异，比率比较治疗和未治疗的受试者之间的连续协变量的方差，比较高阶矩和相互作用，五个数字的总结，以及图形方法，如分位数-分位数图、并排箱线图和非参数密度图，用于比较治疗组间基线协变量的分布。我们描述的方法，以确定抽样分布的标准化差异时，真正的标准化差异等于零，从而允许一个确定的范围内的标准化差异是合理的倾向评分模型已被正确指定。我们强调的局限性，以前使用的一些方法来评估充分的规范的倾向评分模型。特别是，基于比较治疗和未治疗受试者之间的估计倾向评分分布的方法是没有信息的。版权所有© 2009约翰威利父子有限公司。
The propensity score is a subject's probability of treatment, conditional on observed baseline covariates. Conditional on the true propensity score, treated and untreated subjects have similar distributions of observed baseline covariates. Propensity-score matching is a popular method of using the propensity score in the medical literature. Using this approach, matched sets of treated and untreated subjects with similar values of the propensity score are formed. Inferences about treatment effect made using propensity-score matching are valid only if, in the matched sample, treated and untreated subjects have similar distributions of measured baseline covariates. In this paper we discuss the following methods for assessing whether the propensity score model has been correctly specified: comparing means and prevalences of baseline characteristics using standardized differences; ratios comparing the variance of continuous covariates between treated and untreated subjects; comparison of higher order moments and interactions; five-number summaries; and graphical methods such as quantile–quantile plots, side-by-side boxplots, and non-parametric density plots for comparing the distribution of baseline covariates between treatment groups. We describe methods to determine the sampling distribution of the standardized difference when the true standardized difference is equal to zero, thereby allowing one to determine the range of standardized differences that are plausible with the propensity score model having been correctly specified. We highlight the limitations of some previously used methods for assessing the adequacy of the specification of the propensity-score model. In particular, methods based on comparing the distribution of the estimated propensity score between treated and untreated subjects are uninformative. Copyright © 2009 John Wiley & Sons, Ltd.
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影响因子：
4.8
作者：
Austin, Peter C.;Mamdani, Muhammad M.;Tu, Jack V.
通讯作者：
Tu, Jack V.
影响因子：
158.5
作者：
LAVORI, PW;LOUIS, TA;POLANSKY, M
通讯作者：
POLANSKY, M
影响因子：
2
作者：
Austin, Peter C.
通讯作者：
Austin, Peter C.
影响因子：
2
作者：
Austin, PC;Mamdani, MM
通讯作者：
Mamdani, MM
DOI：
10.1111/j.1467-985x.2005.00380.x
发表时间：
2006-01-01
影响因子：
2
作者：
Austin, PC;Tu, JV
通讯作者：
Tu, JV