I am interested in calculating the degrees of freedom for predictor variables in mixed effects (or multi-level) models using the Kenward-Roger approximation (described in this paper here).
Using a function (
get_Lb_ddf()) to "Get adjusted denomintor degress freedom for testing Lb=0 in a linear mixed model where L is a restriction matrix," I obtain one value.
My question is, Do these Kenward-Roger approximation degrees of freedom apply to all of the predictor variables in the model?
I ask, because, naïvely, it seems odd to me for a data-level and a group-level predictor, for example, to have the same degrees of freedom.