fit_brms: Fit a binary model for MRP

In kuriwaki/ccesMRPrun: Using MRP Models from Cleaned CCES and Census Data

Fit a binary model for MRP

Description

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

Usage

fit_brms(
  .formula,
  .data,
  name_ones_as = "yes",
  name_trls_as = "n_response",
  ...
)

Arguments

.formula	Formula in ⁠binary y ~ (1|x1) + (1|x2)⁠ form.
.data	Individual-level dataset
name_ones_as	The name for the variable name for the number of successes
name_trls_as	The name for the variable name of the number of trials
...	Arguments passed on to fit_brms_binomial .prior 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 .cores Number of cores to uses .chains Number of chains to pass on fit_brms .iter Number of total iterations. .warmup Of the iterations, how much are burn-ins. Defaults to half. verbose Whether to show iteration messages .seed seed for randomization to pass into brm .backend The backend argument of brms. Currently only "cmdstanr" .threads The number of threads to do within-chain parallelization. Defaults to not using, which is NULL

Examples

## Not run: 
fit <- fit_brms(response ~ (1|educ) + (1|cd), cces_GA)

## End(Not run)

kuriwaki/ccesMRPrun documentation built on Sept. 24, 2024, 2:15 a.m.