extractAIC.joint

Extract AIC from a joint model fit.

Fit joint models of survival and multivariate longitudinal data. The longitudinal
data is specified by generalised linear mixed models. The joint models are fit via maximum
likelihood using an approximate expectation maximisation algorithm.
Bernhardt (2015) <doi:10.1016/j.csda.2014.11.011>.

James Murray

gmvjoint

Joint Models of Survival and Multivariate Longitudinal Data

extractAIC.joint function

<dl><dt>fit</dt>
<dd>A fitted <code>joint</code> object,</dd>
<dt>scale</dt>
<dd>See <code><a href="/link/extractAIC?package=gmvjoint&version=0.4.0" data-mini-rdoc="gmvjoint::extractAIC">extractAIC</a></code>; not used.</dd>
<dt>k</dt>
<dd>Numeric specifying the "weight" of degrees of freedom (default <code>k=2</code>).</dd>
<dt>conditional</dt>
<dd>Should AIC of conditional or observed log-likelihood be used? Defaults
to <code>conditional = FALSE</code>.</dd>
<dt>...</dt>
<dd>additional arguments (none used).</dd></dl>

Arguments

Extract AIC from a joint model fit. — extractAIC.joint

<dl>

<dt>fit</dt>
<dd>A fitted <code>joint</code> object,</dd>


<dt>scale</dt>
<dd>See <code><a href='https://rdrr.io/r/stats/extractAIC.html'>extractAIC</a></code>; not used.</dd>


<dt>k</dt>
<dd>Numeric specifying the "weight" of degrees of freedom (default <code>k=2</code>).</dd>


<dt>conditional</dt>
<dd>Should AIC of conditional or observed log-likelihood be used? Defaults
to <code>conditional = FALSE</code>.</dd>


<dt>...</dt>
<dd>additional arguments (none used).</dd>

</dl>

extractAIC.joint: Extract AIC from a joint model fit.

Description

Usage

Value

Arguments