How does brms use the given data to adjust the default priors?

[torkar]

Hi,

I think this might answer your question:

Default prior for the intercept in multilevel models is based on the data?

Operating System: Ubuntu 18.04 brms Version: 2.10.0 The default prior that brms generates for the intercept seems to use the mean of the outcome variable for the mean of the prior distribution. I always thought that informing the prior by the data is “double-dipping”, i.e., using the data twice, and leads to overconfident inference. Here some R code to replicate the priors: library(brms) get_intercept_prior <- function(stancode) { code_by_line <- strsplit(stancode, "\n")[[1]] code_by_li…