compute_qoi

Compute Quantities of Interest (GATE, GATEcv, URATE)

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

compute_qoi function

<dl><dt>fit_obj</dt>
<dd>An output object of <code>estimate_itr</code> function from the <code>evalITR</code> package.</dd>
<dt>algorithms</dt>
<dd>Machine learning algorithms</dd></dl>

Arguments

Compute Quantities of Interest (GATE, GATEcv, URATE) — compute_qoi

<dl>

<dt>fit_obj</dt>
<dd>An output object of <code>estimate_itr</code> function from the <code>evalITR</code> package.</dd>


<dt>algorithms</dt>
<dd>Machine learning algorithms</dd>

</dl>

compute_qoi: Compute Quantities of Interest (GATE, GATEcv, URATE)

Description

Usage

Arguments