gee_methods

VarCorr.tern_gee

QIC.tern_gee

Additional methods which can simplify working with the GEE result object.

Generalized estimating equations (GEE) are a popular choice
for analyzing longitudinal binary outcomes. This package provides an
interface for fitting GEE, currently for logistic regression, within
the 'tern' <https://cran.r-project.org/package=tern> framework (Zhu,
Sabanés Bové et al., 2023) and tabulate results easily using 'rtables'
<https://cran.r-project.org/package=rtables> (Becker, Waddell et al.,
2023). It builds on 'geepack' <doi:10.18637/jss.v015.i02> (Højsgaard,
Halekoh and Yan, 2006) for the actual GEE model fitting.

Joe Zhu

tern.gee

Tables and Graphs for Generalized Estimating Equations (GEE)
Model Fits

Daniel Sabanés Bové

Emily de la Rua

F. Hoffmann-La Roche AG 

gee_methods function

<dl><dt>x</dt>
<dd>(<code>tern_gee</code>) result of <code>fit_gee()</code>.</dd>
<dt>sigma</dt>
<dd>an optional numeric value used as a multiplier for the
 standard deviations. The default is <code>x$sigma</code> or <code>1</code>
 depending on <code><a href="/link/class?package=tern.gee&version=0.1.5" data-mini-rdoc="tern.gee::class">class</a>(x)</code>.</dd>
<dt>...</dt>
<dd>further optional arguments passed to other methods (none
 for the methods documented here).</dd>
<dt>object</dt>
<dd>(<code>tern_gee</code>) result of <code>fit_gee()</code>.</dd></dl>

Arguments

Methods for GEE Models — gee_methods

<dl>

<dt>x</dt>
<dd>(<code>tern_gee</code>) result of <code>fit_gee()</code>.</dd>


<dt>sigma</dt>
<dd>an optional numeric value used as a multiplier for the
 standard deviations. The default is <code>x$sigma</code> or <code>1</code>
 depending on <code><a href='https://rdrr.io/r/base/class.html'>class</a>(x)</code>.</dd>


<dt>...</dt>
<dd>further optional arguments passed to other methods (none
 for the methods documented here).</dd>


<dt>object</dt>
<dd>(<code>tern_gee</code>) result of <code>fit_gee()</code>.</dd>

</dl>

gee_methods: Methods for GEE Models

Description

Usage

Value

Arguments