  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.
