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I have a mixed model that includes three different variables: Treatment, Stimulation, and DRG, as well as a random effect with DRG nested under a group ((1|Group/DRG)). I am looking to assess how each variable and their interactions affect Response Amplitude. Here is my model:

RespAmp ~ Treatment * Stim * DRG + (1|Group/DRG)

To note:

  • Treatment has two levels, indicated as 0 and 1 (0 = control, 1 = treated), and I needed to make these categorical.
  • Stimulation has three levels, indicated as 1, 2, and 3, which were also made categorical.
  • DRG has four levels, indicated as 3, 4, 5, and 6, also made as categorical.
  • Response Amplitudes are continuous and made as numeric(see code below).
musc$RespAmp<-as.numeric(musc$RespAmp)
musc$Treatment=as.factor(musc$Treatment)
musc$Stim=as.factor(musc$Stim)
#Use L6 as our 'reference DRG' --> change order of the levels and also convert to factor
musc$DRG<-factor(as.character(musc$DRG), levels = c("6", "5", "4", "3"))

Is it possible to create an estimation plot to visualize comparisons between Response Amplitudes from multiple variables?

For example, if I want to compare Response Amplitudes from Treatment = 0, Stim = 1, DRG = 3 to Treatment = 0, Stim = 3, DRG = 3 .... is it possible to visualize this as an estimation plot?

Or do I need to create a separate dataset with each combination of Treatment+Stim+DRG in order to compare another separate dataset combination of Treatment+Stim+DRG?

My understanding of estimation plots is that you are only visualizing two variables and a response, either as paired or unpaired. Essentially, you are visualizing the difference between means of the two variables, the effect size.

I was just hoping to get some clarification on how to best approach creating estimation plots for several variables, and perhaps my understanding of estimation plots and their use.

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    $\begingroup$ Personally, I would use something like ggeffects() or marginaleffects() to plot the three way interaction. One suggestion - I do not think it makes sense to have DRG in both the fixed and random part of the model. I would remove it from the random effects equation, personally. See: strengejacke.github.io/ggeffects/articles/… and marginaleffects.com/chapters/interactions.html $\endgroup$ Commented Nov 11 at 21:56
  • $\begingroup$ I agree with Erik about plotting suggestions. I also suggest considering whether Stimulation and DRG are better thought of as categorical or ordinal variables (not clear from the information provided but possibly important). $\endgroup$ Commented Nov 18 at 11:35

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