Prints summary of "BiBMA.reg"
ensemble implied by the specified priors and formula
Source: R/check-input-and-settings.R
check_setup.BiBMA.Rd
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.
Usage
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 toprior(distribution = "student", parameters = list(location = 0, scale = 0.58, df = 4))
, based on logOR meta-analytic estimates from the Cochrane Database of Systematic Reviews bartos2023empiricalRoBMA.- priors_heterogeneity
list of prior distributions for the heterogeneity
tau
parameter that will be treated as belonging to the alternative hypothesis. Defaults toprior(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 bartos2023empiricalRoBMA.- 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 toNULL
.- priors_baseline_null
prior distributions for the null hypothesis about intercepts (
pi
) for each study. Defaults to an independent uniform prior distribution for each interceptprior("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 thatparallel = TRUE
also suppresses all messages.- ...
additional arguments.