ei_good

EI iterative estimation via Goodman's Regression

Provides a comprehensive suite of tools for estimating the candidate preferences of racial/ethnic voting blocs in elections. Includes functions for predicting voter race/ethnicity and conducting ecological inference. Race/ethnicity prediction builds on race prediction developed by Imai et al. (2016) <doi:10.1093/pan/mpw001>. Ecological inference methods are based on King (1997) <ISBN: 0691012407>, <https://gking.harvard.edu/eicamera/kinroot.html>; King et. al. (2004) <ISBN: 0521542804>, <https://gking.harvard.edu/files/abs/ecinf04-abs.shtml>.

Ari Decter-Frain

eiCompare

Compares Different Ecological Inference Methods

Loren Collingwood

Hikari Murayama

Pratik Sachdeva

Juandalyn Burke

Scott Henderson

Spencer Wood

Matt Barreto

ei_good function

<dl><dt>data</dt>
<dd>A data.frame() object containing precinct-level turnout data by
race and candidate</dd>
<dt>cand_cols</dt>
<dd>A character vector listing the column names for turnout for
each candidate</dd>
<dt>race_cols</dt>
<dd>A character vector listing the column names for turnout by
race</dd>
<dt>totals_col</dt>
<dd>The name of the column containing total votes cast in each
precinct</dd></dl>

Arguments

Loren Collingwood &lt;loren.collingwood@ucr.edu&gt;
Ari Decter-Frain &lt;agd75@cornell.edu&gt;

Author

EI iterative estimation via Goodman's Regression — ei_good

<dl>

<dt>data</dt>
<dd>A data.frame() object containing precinct-level turnout data by
race and candidate</dd>


<dt>cand_cols</dt>
<dd>A character vector listing the column names for turnout for
each candidate</dd>


<dt>race_cols</dt>
<dd>A character vector listing the column names for turnout by
race</dd>


<dt>totals_col</dt>
<dd>The name of the column containing total votes cast in each
precinct</dd>

</dl>

ei_good: EI iterative estimation via Goodman's Regression

Description

Usage

Value

Arguments

Author

References