Bounds and Sensitivity Analysis of the Causal Effect Under Outcome-Independent MNAR Confounding
Fuente:
arXiv
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| Auteur principal: | |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866909374178394112 |
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| author | Peña, Jose M. |
| author_facet | Peña, Jose M. |
| contents | We report assumption-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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_06726 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Bounds and Sensitivity Analysis of the Causal Effect Under Outcome-Independent MNAR Confounding Peña, Jose M. Methodology Machine Learning We report assumption-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. |
| title | Bounds and Sensitivity Analysis of the Causal Effect Under Outcome-Independent MNAR Confounding |
| topic | Methodology Machine Learning |
| url | https://arxiv.org/abs/2410.06726 |