influence.brma: Measure Influence for brma Objects

In RoBMA: Robust Bayesian Meta-Analyses

Measure Influence for brma Objects

Description

Computes DFFITS, Cook's distance, COVRATIO, and other influence diagnostics for a fitted brma object.

Usage

## S3 method for class 'brma'
influence(model, ...)

Arguments

model	a fitted brma object.
...	additional arguments (currently ignored).

Value

An object of class "infl.brma", which corresponds to the structure of metafor::influence objects. It is a list containing:

inf	A data frame with columns: rstudent, dffits, cook.d, cov.r, tau.del, and hat, where available. The tau.del column is the PSIS leave-one-out posterior mean of the aggregate heterogeneity. For scale models, aggregation is over the remaining scale-model rows after each deletion.
dfbs	A data frame with DFBETAS values for the model coefficients.

Undefined determinant- or variance-standardized diagnostics are reported as NaN and printed with an explanatory note.

See Also

dffits.brma, cooks.distance.brma, covratio.brma, dfbetas.brma, hatvalues.brma

Examples

## Not run: 
if (requireNamespace("metadat", quietly = TRUE)) {
  data(dat.lehmann2018, package = "metadat")
  fit <- brma(
    yi      = yi,
    vi      = vi,
    data    = dat.lehmann2018,
    measure = "SMD",
    seed    = 1,
    silent  = TRUE
  )
  fit <- add_loo(fit)

  inf <- influence(fit)
  print(inf)
}

## End(Not run)

RoBMA documentation built on May 7, 2026, 5:08 p.m.