Bounding the Probabilities of Benefit and Harm Through Sensitivity Parameters and Proxies

Jose M. Peña
3/8/2023
stat.MEcs.LG

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Abstract

We present two methods for bounding the probabilities of benefit and harm under unmeasured confounding. The first method computes the (upper or lower) bound of either probability as a function of the observed data distribution and two intuitive sensitivity parameters which, then, can be presented to the analyst as a 2-D plot to assist her in decision making. The second method assumes the existence of a measured nondifferential proxy (i.e., direct effect) of the unmeasured confounder. Using this proxy, tighter bounds than the existing ones can be derived from just the observed data distribution.

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Cite this paper

@article{pea2023bounding,
  title  = {Bounding the Probabilities of Benefit and Harm Through Sensitivity Parameters and Proxies},
  author = {Jose M. Peña},
  year   = {2023},
  eprint = {2303.05396},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2303.05396v3}
}

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