warts

A dataset comparing immunotherapy to cryotherapy treatments and their effeteness of
removing warts

datasets

Fits a Causal Effect Random Forest of Interaction Tress (CERFIT) which is a modification of the Random Forest algorithm where each split is chosen to maximize subgroup treatment heterogeneity. Doing this allows it to estimate the individualized treatment effect for each observation in either randomized controlled trial (RCT) or observational data. For more information see L. Li, R. A. Levine, and J. Fan (2022) <doi:10.1002/sta4.457>.

Justin Thorp

CERFIT

Causal Effect Random Forest of Interaction Trees

Luo Li

Juanjuan Fan

warts function

A data frame with 180 rows and 8 variables:<dl>
<dt>sex</dt>
<dd>Patients Sex</dd><dt>age</dt>
<dd>Patients Age</dd><dt>Time</dt>
<dd>Time Elapsed Before Treatment</dd><dt>Number_of_Warts</dt>
<dd>Number of Warts</dd><dt>Type</dt>
<dd>Type of Wart</dd><dt>Area</dt>
<dd>Wart Surface Area</dd><dt>Result_of_Treatment</dt>
<dd>Treatment Outcome</dd><dt>treatment</dt>
<dd>0 for immunotherapy and 1 for cryotherapy</dd>
</dl>

Format

Randomized Controlled Trial Warts Dataset — warts

A data frame with 180 rows and 8 variables:<dl>
<dt>sex</dt>
<dd>Patients Sex</dd>

<dt>age</dt>
<dd>Patients Age</dd>

<dt>Time</dt>
<dd>Time Elapsed Before Treatment</dd>

<dt>Number_of_Warts</dt>
<dd>Number of Warts</dd>

<dt>Type</dt>
<dd>Type of Wart</dd>

<dt>Area</dt>
<dd>Wart Surface Area</dd>

<dt>Result_of_Treatment</dt>
<dd>Treatment Outcome</dd>

<dt>treatment</dt>
<dd>0 for immunotherapy and 1 for cryotherapy</dd>


</dl>

warts: Randomized Controlled Trial Warts Dataset

Description

Usage

Arguments

Format