Prints summary of "BiBMA.reg" ensemble implied by the specified priors and formula

Source: R/check-input-and-settings.R

check_setup prints summary of "RoBMA.reg" ensemble implied by the specified prior distributions. It is useful for checking the ensemble configuration prior to fitting all of the models.

check_setup.BiBMA(
  priors_effect = prior(distribution = "student", parameters = list(location = 0, scale =
    0.58, df = 4)),
  priors_heterogeneity = prior(distribution = "invgamma", parameters = list(shape = 1.77,
    scale = 0.55)),
  priors_effect_null = prior(distribution = "point", parameters = list(location = 0)),
  priors_heterogeneity_null = prior(distribution = "point", parameters = list(location =
    0)),
  priors_baseline = NULL,
  priors_baseline_null = prior_factor("beta", parameters = list(alpha = 1, beta = 1),
    contrast = "independent"),
  models = FALSE,
  silent = FALSE,
  ...
)

Arguments

priors_effect

list of prior distributions for the effect size (mu) parameter that will be treated as belonging to the alternative hypothesis. Defaults to prior(distribution = "student", parameters = list(location = 0, scale = 0.58, df = 4)), based on logOR meta-analytic estimates from the Cochrane Database of Systematic Reviews (Bartoš et al. 2023) .

priors_heterogeneity

list of prior distributions for the heterogeneity tau parameter that will be treated as belonging to the alternative hypothesis. Defaults to prior(distribution = "invgamma", parameters = list(shape = 1.77, scale = 0.55)) that is based on heterogeneities of logOR estimates from the Cochrane Database of Systematic Reviews (Bartoš et al. 2023) .

priors_effect_null

list of prior distributions for the effect size (mu) parameter that will be treated as belonging to the null hypothesis. Defaults to a point null hypotheses at zero, prior(distribution = "point", parameters = list(location = 0)).

priors_heterogeneity_null

list of prior distributions for the heterogeneity tau parameter that will be treated as belonging to the null hypothesis. Defaults to a point null hypotheses at zero (a fixed effect meta-analytic models), prior(distribution = "point", parameters = list(location = 0)).

priors_baseline

prior distributions for the alternative hypothesis about intercepts (pi) of each study. Defaults to NULL.

priors_baseline_null

prior distributions for the null hypothesis about intercepts (pi) for each study. Defaults to an independent uniform prior distribution for each intercept prior("beta", parameters = list(alpha = 1, beta = 1), contrast = "independent").

models

should the models' details be printed.

silent

whether all print messages regarding the fitting process should be suppressed. Defaults to TRUE. Note that parallel = TRUE also suppresses all messages.

...

additional arguments.

Value

check_setup.reg invisibly returns list of summary tables.