Summarize report/table bundles in a user-friendly format

Usage

# S3 method for class 'mfrm_bundle'
summary(object, digits = 3, top_n = 10, include_person = FALSE, ...)

Arguments

object: Any report bundle produced by mfrmr table/report helpers.
digits: Number of digits for printed numeric values.
top_n: Number of preview rows shown from the main table component.
include_person: If TRUE, person-level identifiers may appear in supported summary and preview tables. The default suppresses identifier columns, person-facet level labels, and ConQuest case labels from the returned summary object and its console output. This does not alter the source bundle.
...: Reserved for generic compatibility.

Value

An object of class summary.mfrm_bundle.

Details

This method provides a compact summary for bundle-like outputs (for example: unexpected-response, fair-average, chi-square, and category report objects). It extracts:

object class and available components
one-row summary table when available
preview rows from the main data component
resolved settings/options

Branch-aware summaries are provided for:

mfrm_bias_count (branch = "original" / "facets")
mfrm_fixed_reports (branch = "original" / "facets")
mfrm_visual_summaries (branch = "original" / "facets")

Additional class-aware summaries are provided for:

mfrm_unexpected, mfrm_fair_average, mfrm_displacement
mfrm_interrater, mfrm_facets_chisq, mfrm_bias_interaction
mfrm_rating_scale, mfrm_category_structure, mfrm_category_curves
mfrm_measurable, mfrm_unexpected_after_bias, mfrm_output_bundle
mfrm_residual_pca, mfrm_specifications, mfrm_data_quality, mfrm_fit_measures
mfrm_iteration_report, mfrm_subset_connectivity, mfrm_facet_statistics
mfrm_facets_contract_review, mfrm_facets_fit_review, mfrm_facets_fit_df_guide, mfrm_reference_benchmark

Interpreting output

overview: class, component count, and selected preview component.
summary: one-row aggregate block when supplied by the bundle.
preview: first top_n rows from the main table-like component.
settings: resolved option values if available.
validation_scope: package-generated versus independently supplied evidence scope when summarizing mfrm_reference_benchmark.
conquest_command_scope: ConQuest command-template scope when summarizing mfrm_conquest_overlap_bundle.
conquest_output_contract: requested ConQuest outputs and review handoff when summarizing mfrm_conquest_overlap_bundle.
mfrmr_fit_status: actual optimizer controls, MML engine, convergence evidence, and inference-readiness state for an mfrm_conquest_overlap_bundle.
normalization_scope: extracted-table normalization scope when summarizing mfrm_conquest_overlap_tables.
review_scope: supplied-table review scope when summarizing mfrm_conquest_overlap_review.
conquest_overlap_checks / population_policy_checks: specialized benchmark check previews when summarizing mfrm_reference_benchmark.

Typical workflow

Generate a bundle table/report helper output.
Run summary(bundle) for compact QA.
Drill into specific components via $ and visualize with plot(bundle, ...).

Examples

# Long-running workflow; run explicitly when needed.
# example("summary.mfrm_bundle", run.dontrun = TRUE)
if (FALSE) { # \dontrun{
toy_full <- load_mfrmr_data("example_core")
toy_people <- unique(toy_full$Person)[1:12]
toy <- toy_full[toy_full$Person %in% toy_people, , drop = FALSE]
fit <- suppressWarnings(
  fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score", method = "JML", maxit = 30)
)
t4 <- unexpected_response_table(fit, abs_z_min = 1.5, prob_max = 0.4, top_n = 5)
summary(t4)
diag <- diagnose_mfrm(fit, residual_pca = "none")
bias <- estimate_bias(fit, diag, facet_a = "Rater", facet_b = "Criterion", max_iter = 2)
t11 <- bias_count_table(bias, branch = "facets")
summary(t11)
} # }