dof_KR uses an adaptation of the machinery from the pbkrtest package
to compute the Kenward-Roger approximation of the 'denominator degrees of freedom' for
each fixed-effect coefficient in the conditional model; dof_satt does the same
for Satterthwaite approximations
dof_KR(model)dof_satt(model, L = diag(length(fixef(model)$cond)))
a named vector of ddf for each conditional fixed-effect parameter; dof_KR includes attributes 'vcov'
(Kenward-Roger adjusted covariance matrix) and 'se' (the corresponding standard errors)
a fitted glmmTMB object
a by default, equal to an identity matrix (i.e., ddfs are returned for each fixed-effect parameter
Kenward-Roger adjustments should not be used for models fitted with ML rather than REML;
the theory is only well understood, and the model is only tested, for LMMs (family = "gaussian").
Use at your own risk for GLMMs!