get_outcome_weights.dml_with_smoother

Post-estimation command to extract outcome weights for double ML
run with an outcome smoother.

Many treatment effect estimators can be written as weighted outcomes.
These weights have established use cases like checking covariate balancing via packages like 'cobalt'.
This package takes the original estimator objects and outputs these outcome weights.
It builds on the general framework of Knaus (2024) <doi:10.48550/arXiv.2411.11559>.
This version is compatible with the 'grf' package and provides an internal implementation of Double Machine Learning.

Knaus Michael C.

OutcomeWeights

Outcome Weights of Treatment Effect Estimators

Michael C. Knaus

Henri Pfleiderer

get_outcome_weights.dml_with_smoother function

<dl><dt>object</dt>
<dd>An object of class <code>dml_with_smoother</code>, i.e. the result of running <code>dml_with_smoother</code>.</dd>
<dt>...</dt>
<dd>Pass potentially generic get_outcome_weights options.</dd>
<dt>all_reps</dt>
<dd>If <code>TRUE</code>, outcomes weights of each repetitions passed. Default <code>FALSE</code>.</dd></dl>

Arguments

Outcome weights for the dml_with_smoother function — get_outcome_weights.dml_with_smoother

<dl>

<dt>object</dt>
<dd>An object of class <code>dml_with_smoother</code>, i.e. the result of running <code>dml_with_smoother</code>.</dd>


<dt>...</dt>
<dd>Pass potentially generic get_outcome_weights options.</dd>


<dt>all_reps</dt>
<dd>If <code>TRUE</code>, outcomes weights of each repetitions passed. Default <code>FALSE</code>.</dd>

</dl>

get_outcome_weights.dml_with_smoother: Outcome weights for the `dml_with_smoother` function

Description

Usage

Value

Arguments

References