Print Prior Distributions

print_prior prints prior distributions stored in brma, BMA, and RoBMA objects. This is a user-facing helper for inspecting priors without extracting them from the internal $priors list.

Usage

print_prior(x, ...)

# S3 method for class 'prior'
print_prior(x, ...)

# S3 method for class 'brma'
print_prior(x, parameter, parameter_mods, parameter_scale, ...)

Arguments

x

a brma, BMA, or RoBMA object, or a prior distribution object.

...

additional arguments passed to the prior printing method. Use silent = TRUE for programmatic inspection without console output.

parameter

character. Base parameter to print. If omitted, all stored prior distributions are printed. Common options are "mu", "tau", "rho", "PET", "PEESE", "omega", and "bias", with aliases "effect" = "mu", "heterogeneity" = "tau", and "weightfunction" = "omega". GLMM outcome priors "pi" and "phi" are available when present. Moderator and scale terms can also be selected by name when unambiguous. A character vector requests multiple base parameters.

parameter_mods

character. Moderator term to print. Use "intercept" for the adjusted effect in meta-regression models.

parameter_scale

character. Scale-regression term to print. Use "intercept" for the heterogeneity intercept in location-scale models.

Value

print_prior invisibly returns the selected prior distribution. If multiple parameters are requested, a named list of prior distributions is returned invisibly.

See also

plot_prior() BMA() RoBMA() brma() prior()

Examples

if (FALSE) { # \dontrun{
if (requireNamespace("metadat", quietly = TRUE)) {
  data(dat.lehmann2018, package = "metadat")
  priors <- BMA(
    yi          = yi,
    vi          = vi,
    mods        = ~ Preregistered,
    data        = dat.lehmann2018,
    measure     = "SMD",
    only_priors = TRUE
  )

  print_prior(priors)
  print_prior(priors, parameter = "mu")
  print_prior(priors, parameter = "tau")
  print_prior(priors, parameter_mods = "Preregistered")
}
} # }