Internally, it creates a count version of the individual-data via ccesMRPprep::build_counts and then runs the regression in fit_brms_binomial.

  name_ones_as = "yes",
  name_trls_as = "n_response",



Formula in binary y ~ (1|x1) + (1|x2) form.


Individual-level dataset


The name for the variable name for the number of successes


The name for the variable name of the number of trials


Arguments passed on to fit_brms_binomial


prior specification that can be interpreted by brms. The default is a standard normal prior, which is tighter than the brms default but has shown to have good prior posterior draws


Number of cores to uses


Number of chains to pass on fit_brms


Number of total iterations.


Of the iterations, how much are burn-ins. Defaults to half.


Whether to show iteration messages


seed for randomization to pass into brm


The backend argument of brms. Defaults to "rstan", can also be "cmdstanr"


if (FALSE) {
fit <- fit_brms(response ~ (1|educ) + (1|cd), cces_GA)