Very simple question - I am hoping to get some simple clarity on what the
pp_check bar plots are telling me. Here is a
brms example from the documentation
library(brms) fit2 <- brm(rating ~ treat + period + carry, data = inhaler, family = cumulative(), prior = set_prior("normal(0,5)"), refresh = 0) pp_check(fit2, type = 'bars')
This plot is showing the distribution of the ratings 1-4 in the inhaler data (by count) and the predicted number of each rating from the model (median as dot + error bars), i.e. the predicted distribution.
y-rep tells me nothing about the accuracy of the predictions. So the model may predict that many emperical 1’s are actually 2’s, and visa-versa, getting many of the predictions wrong, but I cannot know the accuracy from this plot. Am I thinking of this correctly?