Plotting two-way interactions within a three-way design in brms

I am trying to plot a two-way interaction within a three-way design, but conditional_effects is not quite giving me what I want. Using the example from the function’s help, I can plot the full three-way design nicely:

fit3way <- brm(count ~ zAge * zBase * Trt, data = epilepsy)
conditions <- make_conditions(fit3way, "zAge")
conditional_effects(fit3way, "zBase:Trt", conditions = conditions)

However, I want to plot the credible two-way interaction, collapsing (i.e., averaging) across the third variable of age. In theory I can do that removing the conditions argument from the above, but I noticed that the resulting two-way plot is just the two-way interaction at zAge = 0. I verified this by looking at the data.frames of the plots.

p3way <- conditional_effects(fit3way, "zBase:Trt", conditions = conditions)[[1]]
p3way %>% filter(cond__ == "zAge = 0") %>% head()
p2way <- conditional_effects(fit3way, "zBase:Trt")[[1]]

Basically, is there a way to really ignore the effect of the third variable entirely when plotting this lower-order two-way interaction? Thanks in advance!

  • Operating System: Windows 10 (19043.1706)
  • brms Version: 2.16.3