Describe brms model results

Usage

# S3 method for class 'brmsfit'
apa(
  obj,
  term,
  trans = NULL,
  digits = 2,
  eff.size = FALSE,
  eff.size.type = "r",
  nsamples = 100,
  ci.type = "HPDI",
  ...
)

Arguments

obj: model object from brms::brm
term: model term to describe
trans: an optional function to transform the results to another scale (default: NULL)
digits: number of digits in the output
eff.size: string describing how to compute an effect size (currently, either 'fe_to_all', 'part_fe', or 'part_fe_re')
eff.size.type: type of the effect size ('r' or 'r2')
nsamples: number of samples to use for the effect size computations
ci.type: type of intervals to use (currently, all that is not HPDI is treated as ETI using bayestestR::eti)
...: other parameters passed to format_results

Value

A character result reporting the posterior mean coefficient, its 95% interval, and optionally an effect-size estimate.

Examples

# \donttest{
if (requireNamespace("brms", quietly = TRUE) &&
    requireNamespace("bayestestR", quietly = TRUE)) {
  # Generate sample data
  set.seed(42)
  x <- seq(-1, 1, length.out = 30)
  y <- 1 + 2 * x + rnorm(30, sd = 0.5)
  
  # Fit a Bayesian regression model
  fit <- brms::brm(y ~ x, data = data.frame(x, y), backend = "rstan",
                   chains = 1, cores = 1, iter = 500, seed = 42, refresh = 0)
  print(apa(fit, "x"))
  
  # Convert x to another scale for output
  print(apa(fit, "x", trans = function(val) val + 5))
}
#> Compiling Stan program...
#> Error in .fun(model_code = .x1): Boost not found; call install.packages('BH')
# }