clean_coefficients

Processing to split out base levels and add variable importance to each term. Inspired by `tidycat::tidy_categorical()`, modified for use in prettyglm..

One of the main advantages of using Generalised Linear Models
is their interpretability.  The goal of 'prettyglm' is to provide a
set of functions which easily create beautiful coefficient summaries
which can readily be shared and explained. 'prettyglm' helps users
create coefficient summaries which include categorical base levels,
variable importance and type III p.values. 'prettyglm' also creates
beautiful relativity plots for categorical, continuous and splined
coefficients.

Jared Fowler

prettyglm

Pretty Summaries of Generalized Linear Model Coefficients

clean_coefficients function

<dl><dt>d</dt>
<dd>Data frame <code><a href="https://tibble.tidyverse.org/reference/tibble.html">tibble</a></code> output from <code><a href="https://broom.tidymodels.org/reference/tidy.lm.html">tidy.lm</a></code>; with one row for each term in the regression, including column `term`</dd>
<dt>m</dt>
<dd>Model object <code><a href="/link/glm?package=prettyglm&version=1.0.1" data-mini-rdoc="prettyglm::glm">glm</a></code></dd>
<dt>vimethod</dt>
<dd>Variable importance method. Still in development</dd>
<dt>spline_seperator</dt>
<dd>Sting of the spline separator. For example AGE_0_25 would be "_"</dd>
<dt>...</dt>
<dd>Any additional parameters to be past to <code>vi</code></dd></dl>

Arguments

Author

clean_coefficients — clean_coefficients

<dl>

<dt>d</dt>
<dd>Data frame <code><a href='https://tibble.tidyverse.org/reference/tibble.html'>tibble</a></code> output from <code><a href='https://broom.tidymodels.org/reference/tidy.lm.html'>tidy.lm</a></code>; with one row for each term in the regression, including column `term`</dd>


<dt>m</dt>
<dd>Model object <code><a href='https://rdrr.io/r/stats/glm.html'>glm</a></code></dd>


<dt>vimethod</dt>
<dd>Variable importance method. Still in development</dd>


<dt>spline_seperator</dt>
<dd>Sting of the spline separator. For example AGE_0_25 would be "_"</dd>


<dt>...</dt>
<dd>Any additional parameters to be past to <code>vi</code></dd>

</dl>

clean_coefficients: clean_coefficients

Description

Usage

Value

Arguments

Author

See Also