normalize_cont_y

normalize continuous outcome function

Implementation of the LoTTA (Local Trimmed Taylor Approximation) model
described in "Bayesian Regression Discontinuity Design with Unknown Cutoff"
by Kowalska, van de Wiel, van der Pas (2024) <doi:10.48550/arXiv.2406.11585>.

Julia Kowalska

LoTTA

Bayesian Inference in Regression Discontinuity Designs

normalize_cont_y function

<dl><dt>y</dt>
<dd><ul>
<li>outcome data</li>
</ul></dd>
<dt>x</dt>
<dd><ul>
<li>score data</li>
</ul></dd>
<dt>trimmed</dt>
<dd><ul>
<li>NULL by default, provide vector of values to trim the data</li>
</ul></dd>
<dt>normalize</dt>
<dd><ul>
<li>whether data is to be normalized</li>
</ul></dd></dl>

Arguments

normalize continuous outcome function — normalize_cont_y

<dl>

<dt>y</dt>
<dd><ul>
<li>outcome data</li>
</ul></dd>


<dt>x</dt>
<dd><ul>
<li>score data</li>
</ul></dd>


<dt>trimmed</dt>
<dd><ul>
<li>NULL by default, provide vector of values to trim the data</li>
</ul></dd>


<dt>normalize</dt>
<dd><ul>
<li>whether data is to be normalized</li>
</ul></dd>

</dl>

normalize_cont_y: normalize continuous outcome function

Description

Usage

Value

Arguments