Denominator df in glmer
I can't remember any more where I saw the commentary, but I'm pretty sure that in Walt Stroup's book he mentions that Kenward-Roger seems to work pretty well for GLMMs, even though it doesn't have much theoretical justification (it was developed for LMMs). However, he also mentions somewhere that in order to make it work (i.e. to be able to extract the quantities on which the K-R approximation is based) you have to use a pseudo-likelihood approach (which lme4 doesn't). I agree that the URL Mollie provides should give you useful information (especially the "Df alternatives" section) ...
On 2018-12-06 5:57 a.m., Mollie Brooks wrote:
Hi Diana, Here?s some documentation on that topic. https://bbolker.github.io/mixedmodels-misc/glmmFAQ.html#why-doesnt-lme4-display-denominator-degrees-of-freedomp-values-what-other-options-do-i-have <https://bbolker.github.io/mixedmodels-misc/glmmFAQ.html#why-doesnt-lme4-display-denominator-degrees-of-freedomp-values-what-other-options-do-i-have> cheers, Mollie ??????????? Mollie E. Brooks, Ph.D. Research Scientist National Institute of Aquatic Resources Technical University of Denmark
On 6Dec 2018, at 10:21, Kornbrot, Diana <d.e.kornbrot at herts.ac.uk> wrote: Simple question. How does one obtain denominator df for F testa resulting from glmer? Do not appear in anova() Many thanks Diana
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