test_itr

Provides various statistical methods for evaluating
Individualized Treatment Rules under randomized data. The provided
metrics include Population Average Value (PAV), Population Average
Prescription Effect (PAPE), Area Under Prescription Effect Curve
(AUPEC). It also provides the tools to analyze Individualized
Treatment Rules under budget constraints. Detailed reference in Imai
and Li (2019) <arXiv:1905.05389>.

Michael Lingzhi Li

evalITR

Evaluating Individualized Treatment Rules

Kosuke Imai

Jialu Li

Xiaolong Yang

test_itr function

<dl><dt>fit</dt>
<dd>Fitted model. Usually an output from <code>estimate_itr</code></dd>
<dt>nsim</dt>
<dd>Number of Monte Carlo simulations used to simulate the null distributions. Default is 1000.</dd>
<dt>...</dt>
<dd>Further arguments passed to the function.</dd></dl>

Arguments

Conduct hypothesis tests — test_itr

<dl>

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


<dt>nsim</dt>
<dd>Number of Monte Carlo simulations used to simulate the null distributions. Default is 1000.</dd>


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

</dl>

test_itr: Conduct hypothesis tests

Description

Usage

Value

Arguments