I’m a new user to this is probably a basic question, but I’m trying to figure out how to set priors on specific random intercepts.
brms makes it ridiculously convenient to fit something like this:
brm(bf(response ~ instructions*diagnosis + (1+instructions | subject) + (1+instructions | stimulus)), data=df, family=cumulative("logit"))
In this case, I have prior information about each stimulus (mean and sd of ratings from a large population). Can I specify a gaussian prior on the intercept for each stimulus?
It’s again super convenient to set a prior on the stimulus group, but I’m not sure how to expand #17 to specify parameters for each individual prior. Am I missing something obvious?
15 sd stimulus 16 sd instructionsreappraise stimulus 17 sd Intercept stimulus
- Operating System: MacOS 10.14.1
- brms Version: 2.6.0