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Assessing Impact of Unobserved Confounders with Sensitivity Index Probabilities through Pseudo-Experiments

by   Beilin Jia, et al.

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.


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