bias_pairwise_report: Build a bias pairwise-contrast report
In mfrmr: Estimation and Diagnostics for Many-Facet Measurement Models

bias_pairwise_report

R Documentation

Build a bias pairwise-contrast report

Description

Build a bias pairwise-contrast report

Usage

bias_pairwise_report(
  x,
  diagnostics = NULL,
  facet_a = NULL,
  facet_b = NULL,
  interaction_facets = NULL,
  max_abs = 10,
  omit_extreme = TRUE,
  max_iter = 4,
  tol = 0.001,
  target_facet = NULL,
  context_facet = NULL,
  top_n = 50,
  p_max = 0.05,
  sort_by = c("abs_t", "abs_contrast", "prob")
)

Arguments

`x`	Output from `estimate_bias()` or `fit_mfrm()`.
`diagnostics`	Optional output from `diagnose_mfrm()` (used when `x` is fit).
`facet_a`	First facet name (required when `x` is fit and `interaction_facets` is not supplied).
`facet_b`	Second facet name (required when `x` is fit and `interaction_facets` is not supplied).
`interaction_facets`	Character vector of two or more facets.
`max_abs`	Bound for absolute bias size when estimating from fit.
`omit_extreme`	Omit extreme-only elements when estimating from fit.
`max_iter`	Iteration cap for bias estimation when `x` is fit.
`tol`	Convergence tolerance for bias estimation when `x` is fit.
`target_facet`	Facet whose local contrasts should be compared across the paired context facet. Defaults to the first interaction facet.
`context_facet`	Optional facet to condition on. Defaults to the other facet in a 2-way interaction.
`top_n`	Maximum number of ranked rows to keep.
`p_max`	Flagging cutoff for pairwise p-values.
`sort_by`	Ranking key: `"abs_t"`, `"abs_bias"`, or `"prob"`.

Details

This helper exposes the pairwise contrast table that was previously only reachable through fixed-width output generation. It is available only for 2-way interactions. The pairwise contrast statistic uses a Welch/Satterthwaite approximation and is labeled as a Rasch-Welch comparison in the output metadata.

Value

A named list with:

table: pairwise contrast rows
summary: one-row contrast summary
orientation_audit: interaction-facet sign audit
settings: resolved reporting options

Examples

toy <- load_mfrmr_data("example_bias")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score", method = "JML", maxit = 25)
diag <- diagnose_mfrm(fit, residual_pca = "none")
out <- bias_pairwise_report(fit, diagnostics = diag, facet_a = "Rater", facet_b = "Criterion")
summary(out)

mfrmr documentation built on March 31, 2026, 1:06 a.m.