evaluate_hte

Evaluate Heterogeneous Treatment Effects

Provides various statistical methods for evaluating heterogeneous treatment effects (HTE) in randomized experiments. The package includes tools to estimate uniform confidence bands for estimation of the group average treatment effect sorted by generic machine learning algorithms (GATES). It also provides the tools to identify a subgroup of individuals who are likely to benefit from a treatment the most "exceptional responders" or those who are harmed by it. Detailed reference in Imai and Li (2023) <doi:10.48550/arXiv.2310.07973>.

Michael Lingzhi Li

evalHTE

Evaluating Heterogeneous Treatment Effects

Kosuke Imai

Jialu Li

evaluate_hte function

<dl><dt>fit</dt>
<dd>Fitted model. Usually an output from <code>estimate_hte</code>.</dd>
<dt>...</dt>
<dd>Additional arguments passed to the function.</dd></dl>

Arguments

Evaluate Heterogeneous Treatment Effects — evaluate_hte

<dl>

<dt>fit</dt>
<dd>Fitted model. Usually an output from <code>estimate_hte</code>.</dd>


<dt>...</dt>
<dd>Additional arguments passed to the function.</dd>

</dl>

evaluate_hte: Evaluate Heterogeneous Treatment Effects

Description

Usage

Value

Arguments