Am 16.07.2018 um 15:26 schrieb Voeten, C.C. <c.c.voeten at hum.leidenuniv.nl>:
Hi Sebastian,
Yes, rm.ranef=TRUE will give you precisely this, assuming your random effects are all of the 'fs' and/or 're' category, which is the case for the model you describe.
With rm.ranef=FALSE, you would get the effects specifically for the first subject+item combination in your data set (or, more precisely, whichever of these happened to be the first level in your factor variables for these terms).
Best,
Cesko
-----Oorspronkelijk bericht-----
Van: R-sig-mixed-models [mailto:r-sig-mixed-models-bounces at r-
project.org] Namens Sebastian Sauppe
Verzonden: maandag 16 juli 2018 9:20
Aan: r-sig-mixed-models at r-project.org
Onderwerp: [R-sig-ME] GAMMs: difference smooths in itsadug
Dear list members,
I have a question on the treatment of random effects in plotting difference
smooths for GAMMs with the package itsadug.
I am modelling the time course of binomial data with mgcv::bam. The
simplified formula is: cbind(success, failure) ~ 1 + s(Time, by = Condition) +
s(Subject, Time, bs = ?fs?) + s(Item, Time, bs = ?fs?). The two factor smooths
are supposed to account for the random effects of participants and stimuli in
my experiments.
I would like to use itsadug::plot_diff() to visualize how the two conditions
differ over time. However, I am not quite sure what the rm.ranef argument
argument of this function does. What I basically want to do is to look at the
difference the way one would look at a fixed effect in an GLMER model, i.e.,
looking at the fixed effect of the interaction of Time:Condition after the
variance that can be ascribed to random effects of subjects and items have
been accounted for. Would for this rm.ranef=TRUE or rm.ranef=FALSE be the
right option?
Kind regards,
Sebastian
-----------
Dr. Sebastian Sauppe
Department of Comparative Linguistics, University of Zurich
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