variance_ratio_test

Given vector of observed outcomes and treatment vector, test to see if there is evidence
the variances are different (taking kurtosis into account).

Implements methods developed by Ding, Feller, and Miratrix (2016) <doi:10.1111/rssb.12124> <doi:10.48550/arXiv.1412.5000>,
and Ding, Feller, and Miratrix (2018) <doi:10.1080/01621459.2017.1407322> <doi:10.48550/arXiv.1605.06566>
for testing whether there is unexplained variation in treatment effects across observations, and for characterizing
the extent of the explained and unexplained variation in treatment effects. The package includes wrapper functions
implementing the proposed methods, as well as helper functions for analyzing and visualizing the results of the test.

Ben Fifield

hettx

Fisherian and Neymanian Methods for Detecting and Measuring
Treatment Effect Variation

Peng Ding

Avi Feller

Luke Miratrix

variance_ratio_test function

<dl><dt>Yobs</dt>
<dd>Outcome</dd>
<dt>Z</dt>
<dd>Treatment assignment vector</dd>
<dt>data</dt>
<dd>Dataframe with variables listed in formula and control.formula</dd></dl>

Arguments

Variance ratio test — variance_ratio_test

<dl>

<dt>Yobs</dt>
<dd>Outcome</dd>


<dt>Z</dt>
<dd>Treatment assignment vector</dd>


<dt>data</dt>
<dd>Dataframe with variables listed in formula and control.formula</dd>

</dl>

variance_ratio_test: Variance ratio test

Description

Usage

Arguments

Examples