var_center

<code>var_center</code> computes the univariate assignment variable, <code>x</code> based on the cutoffs of 
 two assignment variables: <code>x1</code> and <code>x2</code>.
This is an internal function and is typically not directly invoked by the user. 
It can be accessed using the triple colon, as in rddapp:::var_center().

Estimation of both single- and multiple-assignment Regression Discontinuity Designs
(RDDs). Provides both parametric (global) and non-parametric (local) estimation choices for
both sharp and fuzzy designs, along with power analysis and assumption checks.
Introductions to the underlying logic and analysis of RDDs are in
Thistlethwaite, D. L., Campbell, D. T. (1960) <doi:10.1037/h0044319> and
Lee, D. S., Lemieux, T. (2010) <doi:10.1257/jel.48.2.281>.

Felix Thoemmes

rddapp

Regression Discontinuity Design Application

Ze Jin

Wang Liao

Irena Papst

Wenyu Zhang

Kimberly Hochstedler

var_center function

<dl><dt>x</dt>
<dd>Data frame or matrix of two assignment variables,
where the first column is <code>x1</code> and the second column is <code>x2</code>.</dd>
<dt>cut</dt>
<dd>A numeric vector of length 2 containing the cutpoints at which assignment to the treatment is determined.
The default is <code>c(0, 0)</code>.</dd>
<dt>t.design</dt>
<dd>A character vector of length 2 specifying the treatment option according to design.
The first entry is for <code>x1</code> and the second entry is for <code>x2</code>. Options are 
<code>"g"</code> (treatment is assigned if <code>x1</code> is greater than its cutoff),
<code>"geq"</code> (treatment is assigned if <code>x1</code> is greater than or equal to its cutoff),
<code>"l"</code> (treatment is assigned if <code>x1</code> is less than its cutoff),
and <code>"leq"</code> (treatment is assigned if <code>x1</code> is less than or equal to its cutoff).
The same options are available for <code>x2</code>.</dd>
<dt>t.plot</dt>
<dd>A logical value indicating whether to calculate the univariate treatment variable, <code>t</code>, and make a plot. The default is <code>FALSE</code>.</dd></dl>

Arguments

Assignment Centering for Multivariate Frontier Regression Discontinuity — var_center

<dl>

<dt>x</dt>
<dd>Data frame or matrix of two assignment variables,
where the first column is <code>x1</code> and the second column is <code>x2</code>.</dd>


<dt>cut</dt>
<dd>A numeric vector of length 2 containing the cutpoints at which assignment to the treatment is determined.
The default is <code>c(0, 0)</code>.</dd>


<dt>t.design</dt>
<dd>A character vector of length 2 specifying the treatment option according to design.
The first entry is for <code>x1</code> and the second entry is for <code>x2</code>. Options are 
<code>"g"</code> (treatment is assigned if <code>x1</code> is greater than its cutoff),
<code>"geq"</code> (treatment is assigned if <code>x1</code> is greater than or equal to its cutoff),
<code>"l"</code> (treatment is assigned if <code>x1</code> is less than its cutoff),
and <code>"leq"</code> (treatment is assigned if <code>x1</code> is less than or equal to its cutoff).
The same options are available for <code>x2</code>.</dd>


<dt>t.plot</dt>
<dd>A logical value indicating whether to calculate the univariate treatment variable, <code>t</code>, and make a plot. The default is <code>FALSE</code>.</dd>

</dl>

var_center: Assignment Centering for Multivariate Frontier Regression Discontinuity

Description

Usage

Value

Arguments