summary.estimateEffect

print.summary.estimateEffect

Create a summary regression table similar to those produced for <code>lm</code>

The Structural Topic Model (STM) allows researchers
to estimate topic models with document-level covariates.
The package also includes tools for model selection, visualization,
and estimation of topic-covariate regressions. Methods developed in
Roberts et. al. (2014) <doi:10.1111/ajps.12103> and
Roberts et. al. (2016) <doi:10.1080/01621459.2016.1141684>. Vignette
is Roberts et. al. (2019) <doi:10.18637/jss.v091.i02>.

Brandon Stewart

Estimation of the Structural Topic Model

Margaret Roberts

Dustin Tingley

Kenneth Benoit

summary.estimateEffect function

<dl><dt>object</dt>
<dd>an object of class <code>"estimateEffect"</code>, usually a result of a call to
<code>estimateEffect</code></dd>
<dt>topics</dt>
<dd>a vector containing the topic numbers for each a summary is to be calculated.
Must be contained in the original <code>estimateEffect</code> object</dd>
<dt>nsim</dt>
<dd>the number of simulations to use per parameter set to calculate the standard error.
Defaults to 500</dd>
<dt>...</dt>
<dd>further arguments passed to or from other methods</dd></dl>

Arguments

Summary for estimateEffect — summary.estimateEffect

<dl>

<dt>object</dt>
<dd>an object of class <code>"estimateEffect"</code>, usually a result of a call to
<code>estimateEffect</code></dd>


<dt>topics</dt>
<dd>a vector containing the topic numbers for each a summary is to be calculated.
Must be contained in the original <code>estimateEffect</code> object</dd>


<dt>nsim</dt>
<dd>the number of simulations to use per parameter set to calculate the standard error.
Defaults to 500</dd>


<dt>...</dt>
<dd>further arguments passed to or from other methods</dd>

</dl>

summary.estimateEffect: Summary for estimateEffect

Description

Usage

Arguments

Details

See Also