Add Flexible Covariate Adjustments for Regression Discontinuity Designs #276
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Add Regression Discontinuity from Fork to Main Repo branch
Update RDD from downstream Repo
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SvenKlaassen
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Dec 2, 2024
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SvenKlaassen
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Just update the docstring of the simple dgp
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Do we want to remove the area yield dgp from the import until we have a tuned version (and example in the gallery)?
Other option is to leave it in here and open a new branch for tuning and updating the docstring
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Maybe we want to exclude this DGP in a release until we have a notebook describing it?
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yes I think this would be the best option
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Description
With this PR we are adding estimators for treatment effects in regression discontinuity designs. The estimators enable covariate adjustments powered by ML. We add a module
doubleml.rddthat contains the estimator classRDFlexthat follows usual package syntax. We also add synthetic DGPs inrdd.datasets. Finally, we includedoubleml.rdd.global_learnerswhich adds the functionality to ignore sample weights inscikit-learnestimators. This is useful to combine global and local estimators in RDD.The new features are explained furtherly in the added documentation notebook.
Reference
The implementation follows this paper.
PR Checklist