get_covbeta

At the optimum the covariance is available as
<code>vcov(lmer-model)</code>. This function computes <code>cov(beta)</code> at non
(RE)ML estimates of <code>varpar</code>.

internal

Computes p-values based on (a) Satterthwaite or
Kenward-Rogers degree of freedom methods and (b) parametric bootstrap
for mixed effects models as implemented in the 'lme4'
package. Implements parametric bootstrap test for generalized linear
mixed models as implemented in 'lme4' and generalized linear
models. The package is documented in the paper by Halekoh and
Højsgaard, (2012, <doi:10.18637/jss.v059.i09>). Please see
'citation("pbkrtest")' for citation details.

Søren Højsgaard

pbkrtest

Parametric Bootstrap, Kenward-Roger and Satterthwaite Based
Methods for Test in Mixed Models

Ulrich Halekoh

get_covbeta function

<dl><dt>varpar</dt>
<dd>variance parameters; <code>varpar = c(theta, sigma)</code>.</dd>
<dt>devfun</dt>
<dd>deviance function as a function of theta only.</dd></dl>

Arguments

Rune Haubo B. Christensen. Adapted to pbkrtest by Søren Højsgaard.

Author

Compute covariance of fixed effect parameters as a function of
variance parameters of a linear mixed model — get_covbeta

<dl>

<dt>varpar</dt>
<dd>variance parameters; <code>varpar = c(theta, sigma)</code>.</dd>


<dt>devfun</dt>
<dd>deviance function as a function of theta only.</dd>

</dl>

get_covbeta: Compute covariance of fixed effect parameters as a function of variance parameters of a linear mixed model

Description

Usage

Value

Arguments

Author