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Compare brma Models Using LOO

Source: R/loo.R
loo_compare.brma.Rd

Compare multiple brma models using LOO-PSIS cross-validation. This is a convenience wrapper around loo_compare.

Usage

# S3 method for class 'brma'
loo_compare(x, ..., unit = "estimate")

Arguments

x

a brma model object (the first model to compare).

...

additional brma model objects or loo objects to compare.

unit

output/deletion unit used when extracting LOO from brma objects.

Value

A matrix of class "compare.loo" as returned by loo_compare.

Details

This function compares models based on their expected out-of-sample predictive performance (ELPD).

Important for model comparison: When comparing models via loo_compare, the selection is based on expected out-of-sample predictive performance. This evaluates how well models predict new observations, not how well they fit the observed data. RoBMA rejects comparisons with different outcome targets/data, unit, or implied conditioning_depth.

See also

loo.brma, loo_compare

Examples

if (FALSE) { # \dontrun{
if (requireNamespace("metadat", quietly = TRUE)) {
  data(dat.lehmann2018, package = "metadat")

  fit_bias <- RoBMA(yi = yi, vi = vi, data = dat.lehmann2018, measure = "SMD")
  fit_nobias <- BMA(yi = yi, vi = vi, data = dat.lehmann2018, measure = "SMD")

  fit_bias <- add_loo(fit_bias)
  fit_nobias <- add_loo(fit_nobias)

  loo_compare(fit_bias, fit_nobias)
  loo_compare(loo(fit_bias), loo(fit_nobias))
}
} # }