Extract method for Robust Bayesian Meta-Analysis Fits

residuals.RoBMA extract residuals based on the RoBMA model. Only available for normal-normal models estimated using the spike-and-slab algorithm (i.e., algorithm = "ss").

Usage

# S3 method for class 'RoBMA'
residuals(
  object,
  conditional = FALSE,
  output_scale = NULL,
  probs = c(0.025, 0.975),
  as_samples = FALSE,
  ...
)

Arguments

object

a fitted RoBMA object

conditional

show the conditional estimates (assuming that the alternative is true). Defaults to FALSE. Only available for type == "ensemble".

output_scale

transform the meta-analytic estimates to a different scale. Defaults to NULL which returns the same scale as the model was estimated on.

probs

quantiles of the posterior samples to be displayed. Defaults to c(.025, .975)

as_samples

whether posterior samples instead of a summary table should be returned. Defaults to FALSE.

...

additional arguments

Value

pooled_effect returns a list of tables of class 'BayesTools_table'.

See also

predict.RoBMA()

Examples

if (FALSE) { # \dontrun{
require(metafor)
dat <- escalc(measure = "OR", ai = tpos, bi = tneg, ci = cpos, di = cneg,
              data = dat.bcg)

# fit meta-regression
robma_dat <- data.frame(
  logOR  = dat$yi,
  se     = sqrt(dat$vi),
  ablat  = dat$ablat,
  alloc  = dat$alloc
)

fit <- NoBMA.reg(~ ablat + alloc, data = robma_dat,
                 seed = 1, algorithm = "ss", parallel = TRUE)

residuals(fit)

} # }