Paper: Doubly robust treatment effect estimation with incomplete confounders

Consistency results for treatment effect estimation with missing values.

We propose two new doubly robust treatment effect estimators handling missing values in the confounders with proven consistency results. These estimators are based on recent results for likelihood-based methods and tree-based methods handling missing values.

For a first version of our paper click here. (First update: 2019-06-25, last update: 2019-06-25.)

And a poster presented at the Data Science Summer School 2019.

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Imke Mayer
PhD Student in Statistics and Applied Mathematics

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