get_covbeta

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

varpar

deviance function as a function of theta only.

devfun

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

internal

Test in mixed effects models. Attention is on mixed
effects models as implemented in the 'lme4' package. For linear
mixed models, this package implements (1) a parametric bootstrap
test, (2) a Kenward-Roger-typ modification of F-tests for linear
mixed effects models and (3) a Satterthwaite-type modification of
F-tests for linear mixed effects models. The package also
implements a parametric bootstrap test for generalized linear
mixed models. The facilities of the package are documented in the
paper by Halehoh 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 cov(beta) as a function of varpar of an LMM — 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 cov(beta) as a function of varpar of an LMM

Description

Usage

Value

Arguments

Author