dr_scores

Constructs doubly-robust scores via K-fold cross-fitting.

Nonparametric data-driven approach to discovering heterogeneous subgroups in a selection-on-observables framework.
'aggTrees' allows researchers to assess whether there exists relevant heterogeneity in treatment effects by generating a sequence of optimal groupings,
one for each level of granularity. For each grouping, we obtain point estimation and inference about the group average treatment effects.
Please reference the use as Di Francesco (2022) <doi:10.2139/ssrn.4304256>.

Riccardo Di Francesco

aggTrees

Aggregation Trees

dr_scores function

<dl><dt>Y</dt>
<dd>Outcome vector.</dd>
<dt>D</dt>
<dd>Treatment assignment vector.</dd>
<dt>X</dt>
<dd>Covariate matrix (no intercept).</dd>
<dt>k</dt>
<dd>Number of folds.</dd></dl>

Arguments

Author

Doubly-Robust Scores — dr_scores

<dl>

<dt>Y</dt>
<dd>Outcome vector.</dd>


<dt>D</dt>
<dd>Treatment assignment vector.</dd>


<dt>X</dt>
<dd>Covariate matrix (no intercept).</dd>


<dt>k</dt>
<dd>Number of folds.</dd>

</dl>

dr_scores: Doubly-Robust Scores

Description

Usage

Value

Arguments

Author

Details