pbkrtest - Test in linear mixed effects models based on parametric
bootstrap approaches and Kenward-Roger modification of F-tests

The pbkrtest package is an R package for tests in linear mixed effects models
based on parametric bootstrap approaches and Kenward-Roger
modification of F-tests

Development versions of the packages may be available here.

2 Performance issues

Calculation of the the adjusted degrees of freedom for the
Kenward-Roger approximation can be computationally demanding because it
requires inversion of an N ×N matrix where N is the number
of observations.
Possible remedies for this:

On linux (ubuntu) I have observed that changing the BLAS to ATLAS-BLAS
generally provides a speed-up with a factor 3-6 (compared with R's
default BLAS). That helps in some situations.

Parametric bootstrap is an alternative, and while also
computationally intensive, parametric bootstrap can be parallelized
(facilities exist in pbkrtest).

Lastly, an alternative to Kenward-Roger is to implement a
Satterthwaites approximation. It is on the todo-list.

3 Reporting unexpected behaviours (bugs)

When reporting unexpected behaviours, bugs etc. in the packages,
PLEASE supply:

A reproducible example in terms of a short code
fragment.

The data. The preferred way of sending the data "mydata" is to copy and paste the result from running
dput(mydata).

The result of running the sessionInfo()
function.

4 FAQ (frequently asked questions)

Q:

Do these methods work for generalized linear mixed models ?

A:

Parametric bootstrap is available for
generalized linear mixed models.
We are not aware of any developments for approximate
F-tests in the spirit of Kenward-Roger for generalized linear
models.

Q:

Are these models implemented for mixed models fitted with
the nlme package?