Bounds and Sensitivity Analysis of the Causal Effect Under Outcome-Independent MNAR Confounding

Jose Peña

Keywords: causal inference, missing data, sensitivity analysis

TL;DR: We report distribution-free bounds for any contrast between the probabilities of the potential outcome under exposure and non-exposure under outcome-independent MNAR confounding.

Abstract: We report distribution-free bounds for any contrast between the probabilities of the potential outcome under exposure and non-exposure when the confounders are missing not at random. We assume that the missingness mechanism is outcome-independent. We also report a sensitivity analysis method to complement our bounds.

Submission Number: 46