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Sensitivity analysis for unmeasured confounding in GRF? #1162

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adeldaoud opened this issue Jun 2, 2022 · 4 comments
Open

Sensitivity analysis for unmeasured confounding in GRF? #1162

adeldaoud opened this issue Jun 2, 2022 · 4 comments
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requires research An issue that needs additional thought and experimentation before it can be implemented.

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@adeldaoud
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I wonder what procedure you recommend for conducting a sensitivity analysis for unmeasured confounding for GRF models?

E.g., I am looking into the sensemakr package but that seems to require that one specifies the ATE estimate and its SE, but it also requires the degrees of freedom (dF). In ML setting (for non-parametric models), it is unclear what dF is.

See my question in the following link, carloscinelli/sensemakr#51

@erikcs
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erikcs commented Jun 7, 2022

Hi @adeldaoud, let's wait and hear what @carloscinelli's thoughts are, this is not something we have spent a lot of time thinking about for GRF.

@erikcs erikcs added the requires research An issue that needs additional thought and experimentation before it can be implemented. label Jun 7, 2022
@carloscinelli
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carloscinelli commented Jun 10, 2022

Hi all, we have recent results that covers ATE estimated using machine learning models, see here: https://arxiv.org/abs/2112.13398

@carloscinelli
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We don't have ready to use software yet, but should be available soon

@adeldaoud
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adeldaoud commented Jun 17, 2022

@carloscinelli thanks. Feel free to ping us in this forum when the software will be available. If you happen to have some tutorial R scripts until the software will be released, then please feel free to share it. I will make sure to cite your arxiv paper.

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