Bin_data

Function that splits the data into bins and computes the average in each bin

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

Bin_data function

<dl><dt>y</dt>
<dd><ul>
<li>is the outcome data</li>
</ul></dd>
<dt>x</dt>
<dd><ul>
<li>is the score data</li>
</ul></dd>
<dt>c</dt>
<dd><ul>
<li>specifies the cutoff point, set to NULL if the binning of the data should be independent from c</li>
</ul></dd>
<dt>binsize</dt>
<dd><ul>
<li>length of the interval that is one bin</li>
</ul></dd></dl>

Arguments

Function that splits the data into bins and computes the average in each bin — Bin_data

<dl>

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


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


<dt>c</dt>
<dd><ul>
<li>specifies the cutoff point, set to NULL if the binning of the data should be independent from c</li>
</ul></dd>


<dt>binsize</dt>
<dd><ul>
<li>length of the interval that is one bin</li>
</ul></dd>

</dl>

Bin_data: Function that splits the data into bins and computes the average in each bin

Description

Usage

Value

Arguments