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Build a bias-interaction plot-data bundle (FACETS Table 13: ranked bias list)

Source: R/api-reports.R
bias_interaction_report.Rd

Bundles the ranked flagged-cells view of a bias-interaction run for downstream printing and plotting. The three sibling reports in this family are intentionally distinct:

  • bias_interaction_report() (this one) = FACETS Table 13: a ranked list of interaction cells with t, bias size, and screening tail area – use when reviewing which (facet_a, facet_b) cells deserve follow-up.

  • bias_iteration_report() = iteration history / convergence trace for the bias recalibration (FACETS Table 9 territory) – use when diagnosing whether the bias run itself stabilised.

  • bias_pairwise_report() = pairwise contrast table for a target facet (FACETS Table 14 territory) – use when comparing levels within a facet while controlling for the other.

Usage

bias_interaction_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,
  top_n = 50,
  abs_t_warn = 2,
  abs_bias_warn = 0.5,
  p_max = 0.05,
  sort_by = c("abs_t", "abs_bias", "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.

top_n

Maximum number of ranked rows to keep.

abs_t_warn

Warning cutoff for absolute t statistics.

abs_bias_warn

Warning cutoff for absolute bias size.

p_max

Warning cutoff for p-values.

sort_by

Ranking key: "abs_t", "abs_bias", or "prob".

Value

A named list with bias-interaction plotting/report components. Class: mfrm_bias_interaction.

Details

Preferred bundle API for interaction-bias diagnostics. The function can:

  • use a precomputed bias object from estimate_bias(), or

  • estimate internally from mfrm_fit + facet specification.

Interpreting output

Focus on ranked rows where multiple screening criteria converge:

  • large absolute t statistic

  • large absolute bias size

  • small screening tail area

The bundle is optimized for downstream summary() and plot_bias_interaction() views.

Typical workflow

  1. Run estimate_bias() (or provide mfrm_fit here).

  2. Build bias_interaction_report(...).

  3. Review summary(out) and visualize with plot_bias_interaction().

See also

estimate_bias(), build_fixed_reports(), plot_bias_interaction()

Examples

if (FALSE) { # interactive()
toy <- load_mfrmr_data("example_bias")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score", method = "JML", maxit = 30)
diag <- diagnose_mfrm(fit, residual_pca = "none")
bias <- estimate_bias(fit, diag, facet_a = "Rater", facet_b = "Criterion", max_iter = 2)
out <- bias_interaction_report(bias, top_n = 10)
summary(out)
p_bi <- plot(out, draw = FALSE)
p_bi$data$plot
}