Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies.
Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies.
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DOI：
10.1002/pst.433
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发表时间：
2011-03
影响因子：
1.5
通讯作者：
Austin, Peter C.
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文献类型：
--
作者：
Austin, Peter C.
关键词：
在比较两种治疗效果的研究中，倾向评分是根据受试者测量的基线协变量分配给一种治疗的概率。倾向得分匹配越来越多地用于利用观察数据来估计暴露的影响。在倾向得分匹配的最常见实现中，形成一对已治疗和未治疗的受试者，其倾向得分最多相差预先指定的量（卡尺宽度）。对于最佳卡尺宽度已经进行了一些研究。我们进行了一系列广泛的蒙特卡洛模拟，以确定用于估计平均值差异（对于连续结果）和风险差异（对于二元结果）的最佳卡尺宽度。在估计平均值差异或风险差异时，我们建议研究人员使用宽度等于倾向得分对数标准差 0.2 的卡尺来匹配倾向得分的对数。当至少一些协变量是连续的时，则该值或接近该值的值可以最小化所得估计治疗效果的均方误差。它还消除了粗略估计器中至少 98% 的偏差，并产生了具有大致正确覆盖率的置信区间。此外，经验型 I 错误率大致正确。当所有协变量都是二元时，卡尺宽度的选择对风险差异和均值差异估计性能的影响要小得多。版权所有 © 2010 约翰威利父子有限公司
In a study comparing the effects of two treatments, the propensity score is the probability of assignment to one treatment conditional on a subject's measured baseline covariates. Propensity-score matching is increasingly being used to estimate the effects of exposures using observational data. In the most common implementation of propensity-score matching, pairs of treated and untreated subjects are formed whose propensity scores differ by at most a pre-specified amount (the caliper width). There has been a little research into the optimal caliper width. We conducted an extensive series of Monte Carlo simulations to determine the optimal caliper width for estimating differences in means (for continuous outcomes) and risk differences (for binary outcomes). When estimating differences in means or risk differences, we recommend that researchers match on the logit of the propensity score using calipers of width equal to 0.2 of the standard deviation of the logit of the propensity score. When at least some of the covariates were continuous, then either this value, or one close to it, minimized the mean square error of the resultant estimated treatment effect. It also eliminated at least 98% of the bias in the crude estimator, and it resulted in confidence intervals with approximately the correct coverage rates. Furthermore, the empirical type I error rate was approximately correct. When all of the covariates were binary, then the choice of caliper width had a much smaller impact on the performance of estimation of risk differences and differences in means. Copyright © 2010 John Wiley & Sons, Ltd.
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影响因子：
2
作者：
Austin, Peter C.
通讯作者：
Austin, Peter C.
影响因子：
2
作者：
Agresti, A;Min, YY
通讯作者：
Min, YY
影响因子：
3.7
作者：
ROSENBAUM, PR;RUBIN, DB
通讯作者：
RUBIN, DB
影响因子：
7.2
作者：
SINCLAIR, JC;BRACKEN, MB
通讯作者：
BRACKEN, MB
影响因子：
2
作者：
Austin, Peter C.
通讯作者：
Austin, Peter C.