Bounds and Sensitivity Analysis of the Causal Effect 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.
Cite
Text
Peña. "Bounds and Sensitivity Analysis of the Causal Effect Under Outcome-Independent MNAR Confounding." Proceedings of the Fourth Conference on Causal Learning and Reasoning, 2025.Markdown
[Peña. "Bounds and Sensitivity Analysis of the Causal Effect Under Outcome-Independent MNAR Confounding." Proceedings of the Fourth Conference on Causal Learning and Reasoning, 2025.](https://mlanthology.org/clear/2025/pena2025clear-bounds/)BibTeX
@inproceedings{pena2025clear-bounds,
title = {{Bounds and Sensitivity Analysis of the Causal Effect Under Outcome-Independent MNAR Confounding}},
author = {Peña, Jose},
booktitle = {Proceedings of the Fourth Conference on Causal Learning and Reasoning},
year = {2025},
pages = {693-703},
volume = {275},
url = {https://mlanthology.org/clear/2025/pena2025clear-bounds/}
}