Priors for category specific terms in ordinal logistic regression

[jasonm]

I didn’t find the answer in my original search, but this question has been previously answered here.

Setting Different Priors on Category-Specific Coefficients

I’m fitting an adjacent categories ordinal model with category-specific effects, and I’d like to set different priors on the per-level coefficients. For a reproducible example, consider the following model: library(brms) library(foreign) dat <- read.dta(“https://stats.idre.ucla.edu/stat/data/ologit.dta”) dat$apply = as.integer(dat$apply) fit1 = brm(bf(apply~cs(gpa)), family = acat(), data = dat, chains = 2) GPA has two coefficients, as expected, but prior_summary(fit1) shows only one possi…