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

# \donttest{
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)
#> mfrmr Unexpected Response Summary 
#>   Class: mfrm_unexpected
#>   Components: 3
#> 
#> Threshold summary
#>  TotalObservations UnexpectedN UnexpectedPercent LowProbabilityN LargeResidualN
#>                192           5             2.604               5              5
#>    Rule AbsZThreshold ProbThreshold
#>  either           1.5           0.4
#> 
#> Flagged responses: table
#>  Row Rater    Criterion Weight Score Observed Expected Residual StdResidual
#>  160   R02     Accuracy      1     1        1    3.071   -2.071      -2.816
#>  130   R03     Language      1     1        1    2.966   -1.966      -2.602
#>   55   R01 Organization      1     1        1    2.937   -1.937      -2.548
#>   48   R04      Content      1     1        1    2.697   -1.697      -2.142
#>  181   R04     Accuracy      1     1        1    2.660   -1.660      -2.087
#>  ObsProb MostLikely MostLikelyProb CategoryGap Surprise           Direction
#>    0.020          3          0.513           2    1.704 Lower than expected
#>    0.029          3          0.515           2    1.538 Lower than expected
#>    0.032          3          0.514           2    1.496 Lower than expected
#>    0.066          3          0.478           2    1.181 Lower than expected
#>    0.073          3          0.469           2    1.139 Lower than expected
#>  FlagLowProbability FlagLargeResidual Severity
#>                TRUE              TRUE    5.519
#>                TRUE              TRUE    5.139
#>                TRUE              TRUE    5.045
#>                TRUE              TRUE    4.323
#>                TRUE              TRUE    4.226
#> 
#> Settings
#>    Setting  Value
#>  abs_z_min    1.5
#>   prob_max    0.4
#>       rule either
#> 
#> Notes
#>  - Unexpected-response summary for quick residual screening.
#>  - Person identifiers are suppressed in this summary. Use `include_person =
#>    TRUE` only under appropriate privacy controls.
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)
#> mfrmr Bias Count Summary
#> 
#> Overview
#>  InteractionFacets InteractionOrder InteractionMode Branch         Style FacetA
#>  Rater x Criterion                2        pairwise facets facets_manual  Rater
#>     FacetB Cells TotalCount MeanCount MedianCount MinCount MaxCount
#>  Criterion    16        192        12          12       12       12
#>  LowCountCells LowCountPercent
#>              0               0
#> 
#> Count distribution
#>  Min Q1 Median Mean Q3 Max
#>   12 12     12   12 12  12
#> 
#> Thresholds
#>         Setting Value
#>  min_count_warn    10
#> 
#> Notes
#>  - FACETS-style branch: table columns mirror the output-contract naming.
# }