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Optimal Caliper Width for Propensity Score Matching of Three Treatment Groups: A Monte Carlo Study

机译:三个治疗组倾向得分匹配的最佳测径宽度:蒙特卡洛研究

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摘要

Propensity score matching is a method to reduce bias in non-randomized and observational studies. Propensity score matching is mainly applied to two treatment groups rather than multiple treatment groups, because some key issues affecting its application to multiple treatment groups remain unsolved, such as the matching distance, the assessment of balance in baseline variables, and the choice of optimal caliper width. The primary objective of this study was to compare propensity score matching methods using different calipers and to choose the optimal caliper width for use with three treatment groups. The authors used caliper widths from 0.1 to 0.8 of the pooled standard deviation of the logit of the propensity score, in increments of 0.1. The balance in baseline variables was assessed by standardized difference. The matching ratio, relative bias, and mean squared error (MSE) of the estimate between groups in different propensity score-matched samples were also reported. The results of Monte Carlo simulations indicate that matching using a caliper width of 0.2 of the pooled standard deviation of the logit of the propensity score affords superior performance in the estimation of treatment effects. This study provides practical solutions for the application of propensity score matching of three treatment groups.
机译:倾向得分匹配是一种减少非随机和观察性研究偏倚的方法。倾向得分匹配主要应用于两个治疗组,而不是多个治疗组,因为影响其应用于多个治疗组的一些关键问题仍未解决,例如匹配距离,基线变量平衡的评估以及最佳卡尺的选择宽度。这项研究的主要目的是比较使用不同卡尺的倾向得分匹配方法,并为三个治疗组选择最佳的卡尺宽度。作者使用从倾向得分对数的合并标准偏差的0.1到0.8的卡尺宽度(以0.1为增量)。通过标准差评估基线变量的平衡。还报告了在不同倾向得分匹配样本中各组之间的估计值的匹配率,相对偏差和均方误差(MSE)。蒙特卡洛模拟的结果表明,使用倾向得分对数的合并标准偏差的0.2的卡尺宽度进行匹配,可在评估治疗效果方面提供出色的性能。本研究为三个治疗组倾向评分匹配的应用提供了实用的解决方案。

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