基于协变量调整非参数方法的治疗效果估计

IF 0.1 Q4 MATHEMATICS
Jiabu Ye, D. Lai
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引用次数: 2

摘要

摘要非参数检验是临床研究中常用的两样本比较检验。然而,与测试相关的治疗效果估计可能并不明显,尤其是在协变量调整下。在本文中,我们通过均方误差和覆盖概率的蒙特卡罗模拟,基于Wilcoxon秩和检验、van Elteren检验、对齐秩检验和Jaeckel,Hettmanberger-McKean检验,评估了协变量调整对估计治疗效果的影响。基于模拟,当协变量失衡严重时,常用的基于ANCOVA的方法对治疗效果没有很好的估计。对齐等级测试似乎在大多数情况下都表现良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimations of treatment effects based on covariate adjusted nonparametric methods
Abstract Nonparametric tests are commonly used tests for two sample comparison in clinical studies. However, the estimation of treatment effects associated with the tests may not be obvious, especially under the covariate adjustment. In this article, we evaluated the effect of covariate adjustment on estimating treatment effects based on the Wilcoxon Rank Sum test, the van Elteren test, aligned rank test, and Jaeckel, Hettmansperger-McKean test through Monte Carlo simulations via mean square error and coverage probability. Based on the simulation, commonly used ANCOVA-based approach do not have good estimation of treatment effect when the covariate imbalance is severe. Aligned rank test seems perform well across most scenarios.
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