论文标题

与依赖受试者的观察数据的获胜比率的因果推断

Causal Inference on Win Ratio for Observational Data with Dependent Subjects

论文作者

Zhang, Di, Wisniewski, Stephen R., Jeong, Jong-Hyeon

论文摘要

复合终点通常被预期使用,临床上相关的终点整体将产生有意义的治疗益处。 WIN比率是一个基于等级的统计量,可以汇总复合端点,从而优先考虑复合端点的重要组成部分。统计统计量的统计推断的最新发展一直集中在独立主题上,而没有任何潜在的混淆。当使用观察数据分析复合终点时,重要的挑战之一就是在基线时混淆。此外,在实践中通常可以看到分层观察数据结构,尤其是在医院内筑巢的患者的多中心研究中。这种层次结构可以在分析中的观测值之间引入潜在的依赖性或聚类效应。为了解决这两个问题时,我们提出了具有校准权重的加权分层因果率估计器。校准的重量产生了平衡的患者级协变量,比较组之间的群集效应分布。我们进行了广泛的仿真研究,并显示了拟议估计量在偏差,​​方差估计,I型误差和功率分析方面的表现,无论基线分配分配以及集群内集群内相关性的分配如何。最后,提出的估计量应用于脑损伤儿童的观察性研究。

Composite endpoints are commonly used with an anticipation that clinically relevant endpoints as a whole would yield meaningful treatment benefits. The win ratio is a rank-based statistic to summarize composite endpoints, allowing prioritizing the important components of the composite endpoints. Recent development in statistical inference for the win ratio statistic has been focusing on independent subjects without any potential confounding. When analyzing composite endpoints using observational data, one of the important challenges is confounding at baseline. Additionally, hierarchical observational data structures are commonly seen in practice, especially in multi-center studies with patients nesting within hospitals. Such hierarchical structure can introduce potential dependency or cluster effects among observations in the analysis. To address these two issues when using the win ratio statistic, we propose a weighted stratified causal win ratio estimator with calibrated weights. The calibrated weights create balanced patient-level covariates and cluster effect distributions between comparison groups. We conducted extensive simulation studies and showed promising performance of the proposed estimator in terms of bias, variance estimation, type I error and power analysis, regardless of the allocation of treatment assignments at baseline and intra-cluster correlations within clusters. Lastly, the proposed estimator was applied to an observational study among children with traumatic brain injury.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源