SKS.stat.cov.rq

Shifted kolmogorov-smirnov statistic with covariates and quantile regression.

Implements methods developed by Ding, Feller, and Miratrix (2016) <doi:10.1111/rssb.12124> <arXiv:1412.5000>,
and Ding, Feller, and Miratrix (2018) <doi:10.1080/01621459.2017.1407322> <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

SKS.stat.cov.rq function

<dl><dt>Y</dt>
<dd>Observed outcome vector</dd>
<dt>Z</dt>
<dd>Treatment assigment vector</dd>
<dt>X</dt>
<dd>Additional pre-treatment covariates to adjust for in estimation, but not to interact with treatment.</dd></dl>

Arguments

SKS.stat.cov.rq — SKS.stat.cov.rq

<dl>

<dt>Y</dt>
<dd>Observed outcome vector</dd>


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


<dt>X</dt>
<dd>Additional pre-treatment covariates to adjust for in estimation, but not to interact with treatment.</dd>

</dl>

SKS.stat.cov.rq: SKS.stat.cov.rq

Description

Usage

Value

Arguments

Examples