Priors for category specific terms in ordinal logistic regression

Interfaces brms
1

Is it possible to create separate priors for each coefficient in an ordinal logistic regression model that uses category specific terms? For example, in the model below, I would like a separate prior for each of the the var_aB[1] and var_aB[2] terms.

Looking at the results of get_prior() and prior_summary(), I don’t see any way to distinguish between the coefficients when setting a prior.

I have tried setting priors using something like:
priors ← c(prior(student_t(5, 2, 1), class = b, coef = var_aB[1]),
prior(student_t(5, 0, 1), class = b, coef = var_aB[2])
but this doesn’t seem to work.

I am using Windows 10 and brms 2.15.0.

library(brms)

dat <- data.frame(var_a = factor(rep(c('A', 'B'), times = 50),
                                 levels = c('A', 'B')),
                  var_b = rep(c(1, 2, 1, 2), times = 25),
                  response = factor(sample(c('low', 'mid', 'high'), size = 100, 
                                 replace = TRUE), ordered = TRUE,
                                 levels = c('low', 'mid', 'high'))) 

# Not the priors I want. Just using these as defaults.
priors <- c(prior(student_t(5, 0, 1), class = b))

# Model with category specific terms
mod <- brm(response ~ cs(var_a) + cs(var_b) + cs(var_a:var_b),
           prior = priors,
           family = cratio(),
           data = dat,
           chains = 4, cores = 4,
           seed = 77777)

# Model results. I want to be able to have separate priors for the [1] and [2] parts of each term.
summary(mod)

Please let me know if setting separate priors for each category specific term is possible, and, if so, how to do it.

Thank you.

2

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