论文标题
通过伪证实评估未观察到的混杂因素的影响
Assessing Impact of Unobserved Confounders with Sensitivity Index Probabilities through Pseudo-Experiments
论文作者
论文摘要
未观察到的混杂因素是使用倾向评分方法在因果推理中的长期问题。这项研究提出了非参数指数，以量化未观察到的混杂因素的影响，并与现实世界中的应用相关。研究发现表明，提出的指标可以反映混杂因素的真正影响。希望这项研究能够进一步讨论这一重要问题，并有助于推动因果推断的科学。
Unobserved confounders are a long-standing issue in causal inference using propensity score methods. This study proposed nonparametric indices to quantify the impact of unobserved confounders through pseudo-experiments with an application to real-world data. The study finding suggests that the proposed indices can reflect the true impact of confounders. It is hoped that this study will lead to further discussion on this important issue and help move the science of causal inference forward.
