prPhEstimate

The function uses predict if not specified contrast
in order to attain the estimate, upper, and lower
confidence interval

internal

Methods for manipulating regression models and for describing these in a style adapted for medical journals.
Contains functions for generating an HTML table with crude and adjusted estimates, plotting hazard ratio, plotting model
estimates and confidence intervals using forest plots, extending this to comparing multiple models in a single forest plots.
In addition to the descriptive methods, there are functions for the robust covariance matrix provided by the 'sandwich'
package, a function for adding non-linearities to a model, and a wrapper around the 'Epi' package's Lexis() functions for
time-splitting a dataset when modeling non-proportional hazards in Cox regressions.

Max Gordon

Greg

Regression Helper Functions

Reinhard Seifert

prPhEstimate function

<dl><dt>model</dt>
<dd>The fit of the model to be plotted</dd>
<dt>term.label</dt>
<dd>The name of the label</dd>
<dt>ylog</dt>
<dd>If the outcome should be presented in the anti-log form, i.e.
<code><a href="/link/exp()?package=Greg&version=2.0.2" data-mini-rdoc="Greg::exp()">exp()</a></code>.</dd>
<dt>cntrst</dt>
<dd>A boolean that indicates if the <code>contrast()</code>
function is to be deployed for rms generated functions. The nice
thing is that you get the median as a reference by default.</dd>
<dt>xlim</dt>
<dd>The xlim if provided</dd>
<dt>new_data</dt>
<dd>If not provided the function looks for the most common values
i.e. median for continuous and mode for factors.</dd></dl>

Arguments

Gets the non-linear function's estimate — prPhEstimate

<dl>

<dt>model</dt>
<dd>The fit of the model to be plotted</dd>


<dt>term.label</dt>
<dd>The name of the label</dd>


<dt>ylog</dt>
<dd>If the outcome should be presented in the anti-log form, i.e.
<code><a href='https://rdrr.io/r/base/Log.html'>exp()</a></code>.</dd>


<dt>cntrst</dt>
<dd>A boolean that indicates if the <code>contrast()</code>
function is to be deployed for rms generated functions. The nice
thing is that you get the median as a reference by default.</dd>


<dt>xlim</dt>
<dd>The xlim if provided</dd>


<dt>new_data</dt>
<dd>If not provided the function looks for the most common values
i.e. median for continuous and mode for factors.</dd>

</dl>

prPhEstimate: Gets the non-linear function's estimate

Description

Usage

Value

Arguments