倾向分析下的共变量调整非参数方法

Jiabu Ye, Dejian Lai
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引用次数: 0

摘要

倾向得分是统计推断中调整协变量效应最常用的得分函数之一。在某些预设协变量严重不平衡的情况下,了解倾向得分的影响非常重要。在本文中,我们对使用倾向得分或其他协变量调整的若干非参数双样本检验中,在协变量不平衡情况下的经验类型1误差和经验功率进行了模拟评估。我们的结果表明,在协变量严重失衡或模型规范错误的情况下,常见的倾向得分方法可能会出现类型1错误膨胀。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Covariate adjusted nonparametric methods under propensity analysis
Propensity score is one of the most commonly used score functions in adjusting for covariates effect in statistical inference. It is important to understand the impact with propensity score in case some of the prespecified covariates are severely imbalanced. In this article, we performed simulation evaluation the empirical type 1 error and empirical power under scenario of imbalanced covariates in several nonparametric two sample tests with propensity score or with other covariate adjustments. Our results suggest common propensity score approaches might have type 1 error inflation at scenarios with severe imbalanced covariates or model is mis-specified.
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