getPosterior

Get the posterior probability of a match for each matched pair of observations

Implements a Fellegi-Sunter probabilistic record linkage model that allows for missing data
and the inclusion of auxiliary information. This includes functionalities to conduct a merge of two
datasets under the Fellegi-Sunter model using the Expectation-Maximization algorithm. In addition,
tools for preparing, adjusting, and summarizing data merges are included. The package implements methods
described in Enamorado, Fifield, and Imai (2019) ''Using a Probabilistic Model to Assist Merging of
Large-scale Administrative Records'' <doi:10.1017/S0003055418000783> and is available
at <https://imai.fas.harvard.edu/research/linkage.html>.

Ted Enamorado

fastLink

Fast Probabilistic Record Linkage with Missing Data

Ben Fifield

Kosuke Imai

getPosterior function

<dl><dt>matchesA</dt>
<dd>A dataframe of the matched observations in
dataset A, with all variables used to inform the match.</dd>
<dt>matchesB</dt>
<dd>A dataframe of the matched observations in
dataset B, with all variables used to inform the match.</dd>
<dt>EM</dt>
<dd>The EM object from <code>emlinkMARmov()</code></dd>
<dt>patterns</dt>
<dd>The output from <code>getPatterns()</code>.</dd></dl>

Arguments

Ben Fifield &lt;benfifield@gmail.com&gt;

Author

getPosterior — getPosterior

<dl>

<dt>matchesA</dt>
<dd>A dataframe of the matched observations in
dataset A, with all variables used to inform the match.</dd>


<dt>matchesB</dt>
<dd>A dataframe of the matched observations in
dataset B, with all variables used to inform the match.</dd>


<dt>EM</dt>
<dd>The EM object from <code>emlinkMARmov()</code></dd>


<dt>patterns</dt>
<dd>The output from <code>getPatterns()</code>.</dd>

</dl>

getPosterior: getPosterior

Description

Usage

Value

Arguments

Author