connect_means

`connect_means` connects the means to the modelsummary dataframe.

Create an automated regression table that is well-suited for models that are estimated with multiple dependent variables. 'panelsummary' extends 'modelsummary' (Arel-Bundock, V. (2022) <doi:10.18637/jss.v103.i01>) by allowing regression tables to be split into multiple sections with a simple function call. Utilize familiar arguments such as fmt, estimate, statistic, vcov, conf_level, stars, coef_map, coef_omit, coef_rename, gof_map, and gof_omit from 'modelsummary' to clean the table, and additionally, add a row for the mean of the dependent variable without external manipulation.

Michael Topper

panelsummary

Create Publication-Ready Regression Tables with Panels

Vincent Arel-Bundock

connect_means function

<dl><dt>panel_df</dt>
<dd>The modelsummary dataframe supplied from modelsummary::modelsummary(x, output = "data.frame")</dd>
<dt>means</dt>
<dd>The list of named vectors of means which correspond to each model.</dd></dl>

Arguments

Merges the means to the modelsummary output dataframe — connect_means

<dl>

<dt>panel_df</dt>
<dd>The modelsummary dataframe supplied from modelsummary::modelsummary(x, output = "data.frame")</dd>


<dt>means</dt>
<dd>The list of named vectors of means which correspond to each model.</dd>

</dl>

connect_means: Merges the means to the modelsummary output dataframe

Description

Usage

Value

Arguments