Dear all
I hope you?re doing well. I posted a similar question earlier but didn?t get a reply and because I?m under a bit of pressure to advance on this matter, I hope it?s fine I ask this modified, shorter question on the same topic.
If I have a simple GLMM specified as: diversity ~ land use type + (1|location) where land use type has 4 levels (let?s say 1 control and 3 treatments) and location at least 8.
How could I obtain parametric bootstrap confidence intervals and associated p-values for the difference in mean diversity between each of the treatments and the control, that are corrected for these multiple comparisons by a Dunnett correction?
(So I'm basically looking for a parametric bootstrapping alternative to emmeans' "confint(contrast(emmeans(fitted_model, ~ landuse), "trt.vs.ctrl", ref = 1))")
Any help would be greatly appreciated!
Have a very nice day!
Lieke