educational

A simulated dataset containing the grades and other attributes of 1000
simulated students

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

educational function

A data frame with 1000 rows and 7 variables:<dl>
<dt>SAT_MATH</dt>
<dd>SAT Math Score</dd><dt>HSGPA</dt>
<dd>High School GPA</dd><dt>AGE</dt>
<dd>Age of Student</dd><dt>GENDER</dt>
<dd>Gender of Student</dd><dt>URM</dt>
<dd>Under Represented Minority</dd><dt>A</dt>
<dd>Treatment Variable</dd><dt>Y</dt>
<dd>Students Final Grade</dd>
</dl>

Format

Observational Educational Dataset — educational

A data frame with 1000 rows and 7 variables:<dl>
<dt>SAT_MATH</dt>
<dd>SAT Math Score</dd>

<dt>HSGPA</dt>
<dd>High School GPA</dd>

<dt>AGE</dt>
<dd>Age of Student</dd>

<dt>GENDER</dt>
<dd>Gender of Student</dd>

<dt>URM</dt>
<dd>Under Represented Minority</dd>

<dt>A</dt>
<dd>Treatment Variable</dd>

<dt>Y</dt>
<dd>Students Final Grade</dd>


</dl>

educational: Observational Educational Dataset

Description

Usage

Arguments

Format