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New multivariate tests for assessing covariate balance in matched observational studies
Biometrics ( IF 1.4 ) Pub Date : 2020-10-19 , DOI: 10.1111/biom.13395
Hao Chen 1 , Dylan S Small 2
Affiliation  

We propose new tests for assessing whether covariates in a treatment group and matched control group are balanced in observational studies. The tests exhibit high power under a wide range of multivariate alternatives, some of which existing tests have little power for. The asymptotic permutation null distributions of the proposed tests are studied and the P-values calculated through the asymptotic results work well in simulation studies, facilitating the application of the test to large data sets. The tests are illustrated in a study of the effect of smoking on blood lead levels. The proposed tests are implemented in an R package BalanceCheck.

中文翻译:

用于评估匹配观察研究中协变量平衡的新多变量检验

我们提出了新的测试来评估观察研究中治疗组和匹配对照组的协变量是否平衡。这些测试在广泛的多变量替代方案下表现出很高的功效,其中一些现有的测试几乎没有功效。研究了所提出的测试的渐近置换零分布,通过渐近结果计算的P值在模拟研究中表现良好,有助于将测试应用于大型数据集。这些测试在一项关于吸烟对血铅水平影响的研究中得到了说明。建议的测试在RBalanceCheck中实现。
更新日期:2020-10-19
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