summary.get_outcome_weights

Calculates several summary measures of potentially many outcome weights.

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

summary.get_outcome_weights function

<dl><dt>object</dt>
<dd>get_outcome_weights object.</dd>
<dt>quiet</dt>
<dd>If TRUE, results are passed but not printed.</dd>
<dt>digits</dt>
<dd>Number of digits to be displayed. Default 4.</dd>
<dt>epsilon</dt>
<dd>Threshold below which in absolute values non-zero but small values should be displayed as &lt; ...</dd>
<dt>...</dt>
<dd>further arguments passed to <code>printCoefmat</code></dd></dl>

Arguments

summary method for class outcome_weights — summary.get_outcome_weights

<dl>

<dt>object</dt>
<dd>get_outcome_weights object.</dd>


<dt>quiet</dt>
<dd>If TRUE, results are passed but not printed.</dd>


<dt>digits</dt>
<dd>Number of digits to be displayed. Default 4.</dd>


<dt>epsilon</dt>
<dd>Threshold below which in absolute values non-zero but small values should be displayed as &lt; ...</dd>


<dt>...</dt>
<dd>further arguments passed to <code>printCoefmat</code></dd>

</dl>

summary.get_outcome_weights: `summary` method for class `outcome_weights`

Description

Usage

Value

Arguments