Package index • mfrmr

Guide Pages

mfrmr_workflow_methods: mfrmr Workflow and Method Map
mfrmr_visual_diagnostics: mfrmr Visual Diagnostics Map
mfrmr_reports_and_tables: mfrmr Reports and Tables Map
mfrmr_reporting_and_apa: mfrmr Reporting and APA Guide
mfrmr_linking_and_dff: mfrmr Linking and DFF Guide
mfrmr_compatibility_layer: mfrmr Compatibility Layer Map

Estimation

mfrmr mfrmr-package: mfrmr: Many-Facet Rasch Modeling in R
fit_mfrm(): Fit a many-facet Rasch model with a flexible number of facets
analyze_residual_pca(): Run exploratory residual PCA summaries
mfrm_threshold_profiles(): List literature-based warning threshold profiles
diagnose_mfrm(): Compute diagnostics for an mfrm_fit object
estimate_bias(): Estimate legacy-compatible bias/interaction terms iteratively
compare_mfrm(): Compare two or more fitted MFRM models
compute_information(): Compute design-weighted precision curves for RSM fits
as.data.frame(<mfrm_fit>): Convert mfrm_fit to a tidy data.frame

Simulation and Prediction

build_mfrm_sim_spec(): Build an explicit simulation specification for MFRM design studies
extract_mfrm_sim_spec(): Derive a simulation specification from a fitted MFRM object
simulate_mfrm_data(): Simulate long-format many-facet Rasch data for design studies
evaluate_mfrm_design(): Evaluate MFRM design conditions by repeated simulation
evaluate_mfrm_signal_detection(): Evaluate DIF power and bias-screening behavior under known simulated signals
recommend_mfrm_design(): Recommend a design condition from simulation results
predict_mfrm_population(): Forecast population-level MFRM operating characteristics for one future design
predict_mfrm_units(): Score future or partially observed units under a fixed MML calibration
sample_mfrm_plausible_values(): Sample approximate plausible values under a fixed MML calibration

Reports and Tables

specifications_report(): Build a specification summary report (preferred alias)
data_quality_report(): Build a data quality summary report (preferred alias)
estimation_iteration_report(): Build an estimation-iteration report (preferred alias)
bias_iteration_report(): Build a bias-iteration report
bias_pairwise_report(): Build a bias pairwise-contrast report
subset_connectivity_report(): Build a subset connectivity report (preferred alias)
facet_statistics_report(): Build a facet statistics report (preferred alias)
facet_quality_dashboard(): Facet-quality dashboard for facet-level screening
measurable_summary_table(): Build a measurable-data summary
rating_scale_table(): Build a rating-scale diagnostics report
unexpected_response_table(): Build an unexpected-response screening report
unexpected_after_bias_table(): Build an unexpected-after-adjustment screening report
fair_average_table(): Build an adjusted-score reference table bundle
displacement_table(): Compute displacement diagnostics for facet levels
interrater_agreement_table(): Build an inter-rater agreement report
facets_chisq_table(): Build facet variability diagnostics with fixed/random reference tests
bias_count_table(): Build a bias-cell count report
bias_interaction_report(): Build a bias-interaction plot-data bundle (preferred alias)
category_structure_report(): Build a category structure report (preferred alias)
category_curves_report(): Build a category curve export bundle (preferred alias)

Integrated Outputs

build_mfrm_manifest(): Build a reproducibility manifest for an MFRM analysis
build_mfrm_replay_script(): Build a package-native replay script for an MFRM analysis
build_fixed_reports(): Build legacy-compatible fixed-width text reports
build_apa_outputs(): Build APA text outputs from model results
build_visual_summaries(): Build warning and narrative summaries for visual outputs
apa_table(): Build APA-style table output using base R structures
export_mfrm(): Export MFRM results to CSV files
export_mfrm_bundle(): Export an analysis bundle for sharing or archiving
precision_audit_report(): Build a precision audit report
reporting_checklist(): Build an auto-filled MFRM reporting checklist
run_qc_pipeline(): Run automated quality control pipeline
reference_case_audit(): Build a package-native reference audit for report completeness
reference_case_benchmark(): Benchmark packaged reference cases
print(<mfrm_apa_text>): Print APA narrative text with preserved line breaks
summary(<mfrm_fit>): Summarize an mfrm_fit object in a user-friendly format
summary(<mfrm_diagnostics>): Summarize an mfrm_diagnostics object in a user-friendly format
summary(<mfrm_bias>): Summarize an mfrm_bias object in a user-friendly format
summary(<apa_table>): Summarize an APA/FACETS table object
summary(<mfrm_apa_outputs>): Summarize APA report-output bundles
summary(<mfrm_anchor_audit>): Summarize an anchor-audit object
summary(<mfrm_bundle>): Summarize report/table bundles in a user-friendly format
summary(<mfrm_data_description>): Summarize a data-description object
summary(<mfrm_design_evaluation>): Summarize a design-simulation study
summary(<mfrm_facet_dashboard>): Summarize a facet-quality dashboard
summary(<mfrm_facets_run>): Summarize a legacy-compatible workflow run
summary(<mfrm_signal_detection>): Summarize a DIF/bias screening simulation
summary(<mfrm_population_prediction>): Summarize a population-level design forecast
summary(<mfrm_unit_prediction>): Summarize posterior unit scoring output
summary(<mfrm_plausible_values>): Summarize approximate plausible values from fixed-calibration scoring
summary(<mfrm_threshold_profiles>): Summarize threshold-profile presets for visual warning logic

Plotting

plot(<apa_table>): Plot an APA/FACETS table object using base R
plot(<mfrm_anchor_audit>): Plot an anchor-audit object
plot(<mfrm_fit>): Plot fitted MFRM results with base R
plot(<mfrm_bundle>): Plot report/table bundles with base R defaults
plot(<mfrm_data_description>): Plot a data-description object
plot(<mfrm_design_evaluation>): Plot a design-simulation study
plot(<mfrm_facets_run>): Plot outputs from a legacy-compatible workflow run
plot(<mfrm_signal_detection>): Plot DIF/bias screening simulation results
plot_bias_interaction(): Plot bias interaction diagnostics (preferred alias)
plot_bubble(): Bubble chart of measure estimates and fit statistics
plot_facet_quality_dashboard(): Plot a facet-quality dashboard
plot_information(): Plot design-weighted precision curves
plot_qc_dashboard(): Plot a base-R QC dashboard
plot_qc_pipeline(): Plot QC pipeline results
plot_unexpected(): Plot unexpected responses using base R
plot_fair_average(): Plot fair-average diagnostics using base R
plot_displacement(): Plot displacement diagnostics using base R
plot_interrater_agreement(): Plot inter-rater agreement diagnostics using base R
plot_facets_chisq(): Plot facet variability diagnostics using base R
plot_residual_pca(): Visualize residual PCA results
plot_wright_unified(): Plot a unified Wright map with all facets on a shared logit scale

Linking, DFF, and Anchors

analyze_dff() analyze_dif(): Differential facet functioning analysis
analyze_facet_equivalence(): Analyze practical equivalence within a facet
dif_interaction_table(): Compute interaction table between a facet and a grouping variable
dif_report(): Generate a differential-functioning interpretation report
plot_dif_heatmap(): Plot a differential-functioning heatmap
plot_facet_equivalence(): Plot facet-equivalence results
anchor_to_baseline() print(<mfrm_anchored_fit>) summary(<mfrm_anchored_fit>) print(<summary.mfrm_anchored_fit>): Fit new data anchored to a baseline calibration
detect_anchor_drift() print(<mfrm_anchor_drift>) summary(<mfrm_anchor_drift>) print(<summary.mfrm_anchor_drift>): Detect anchor drift across multiple calibrations
build_equating_chain() print(<mfrm_equating_chain>) summary(<mfrm_equating_chain>) print(<summary.mfrm_equating_chain>): Build a screened linking chain across ordered calibrations
plot_anchor_drift(): Plot anchor drift or a screened linking chain
estimate_all_bias(): Estimate bias across multiple facet pairs

Data and Anchors

ej2021_data ej2021_study1 ej2021_study2 ej2021_combined ej2021_study1_itercal ej2021_study2_itercal ej2021_combined_itercal: Simulated MFRM datasets based on Eckes and Jin (2021)
mfrmr_example_data mfrmr_example_core mfrmr_example_bias: Purpose-built example datasets for package help pages
describe_mfrm_data(): Summarize MFRM input data (TAM-style descriptive snapshot)
audit_mfrm_anchors(): Audit and normalize anchor/group-anchor tables
make_anchor_table(): Build an anchor table from fitted estimates
list_mfrmr_data(): List packaged simulation datasets
load_mfrmr_data(): Load a packaged simulation dataset

Compatibility Layer

run_mfrm_facets() mfrmRFacets(): Run a legacy-compatible estimation workflow wrapper
build_fixed_reports(): Build legacy-compatible fixed-width text reports
facets_output_file_bundle(): Build a legacy-compatible output-file bundle (GRAPH= / SCORE=)
facets_parity_report(): Build a FACETS compatibility-contract audit