[R-sig-ME] GAMMs: difference smooths in itsadug

[Voeten, C.C.]

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 using r-
> project.org] Namens Sebastian Sauppe
> Verzonden: maandag 16 juli 2018 9:20
> Aan: r-sig-mixed-models using 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
> Homepage: https://sites.google.com/site/sauppes/
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