Summarize a facet-quality dashboard
Usage
# S3 method for class 'mfrm_facet_dashboard'
summary(object, digits = 3, top_n = 10, ...)Arguments
- object
Output from
facet_quality_dashboard().- digits
Number of digits for printed numeric values.
- top_n
Number of flagged levels to preview.
- ...
Reserved for generic compatibility.
Examples
toy <- load_mfrmr_data("example_core")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score", method = "JML", maxit = 25)
diag <- diagnose_mfrm(fit, residual_pca = "none")
summary(facet_quality_dashboard(fit, diagnostics = diag))
#> mfrmr Facet Quality Dashboard Summary
#>
#> Overview
#> Facet FacetSource Levels FlaggedLevels BiasSourceBundles
#> Rater inferred 4 2 0
#>
#> Summary
#> Facet Levels MeanEstimate SD MinEstimate MaxEstimate MeanInfit MeanOutfit
#> Rater 4 0 0.313 -0.329 0.334 0.994 1.019
#> SeverityFlagged MisfitFlagged CentralTendencyFlagged BiasFlagged AnyFlagged
#> 0 0 2 0 2
#> BiasRows
#> 0
#>
#> Flagged levels
#> Facet Level Estimate N.x SE ModelSE RealSE SE_Method
#> Rater R01 -0.196 192 0.097 0.097 0.100 Observation-table information
#> Rater R03 0.191 192 0.097 0.097 0.097 Observation-table information
#> Converged PrecisionTier SupportsFormalInference SEUse
#> TRUE exploratory FALSE screening_only
#> TRUE exploratory FALSE screening_only
#> CIBasis CIUse N.y Infit
#> Normal interval from exploratory observation-table SE screening_only 192 1.051
#> Normal interval from exploratory observation-table SE screening_only 192 0.965
#> Outfit InfitZSTD OutfitZSTD DF_Infit DF_Outfit N.x.x ObservedAverage
#> 1.045 0.410 0.468 105.575 192 192 2.609
#> 0.970 -0.213 -0.258 105.705 192 192 2.396
#> ExpectedAverage Bias MeanResidual MeanStdResidual MeanAbsStdResidual ChiSq
#> 2.609 0 0 -0.009 0.842 200.635
#> 2.396 0 0 0.001 0.812 186.334
#> ChiDf ChiP SE_Residual t_Residual p_Residual SE_StdResidual t_StdResidual
#> 191 0.302 0.054 -0.002 0.998 0.072 -0.124
#> 191 0.582 0.054 -0.004 0.997 0.072 0.010
#> p_StdResidual DF PTMEA N.y.y CI_Lower CI_Upper CIEligible
#> 0.901 191 0.623 192 -0.387 -0.005 FALSE
#> 0.992 191 0.658 192 0.000 0.382 FALSE
#> CILabel N AbsEstimate SeverityFlag MisfitFlag
#> Approximate interval; screening only 192 0.196 FALSE FALSE
#> Approximate interval; screening only 192 0.191 FALSE FALSE
#> CentralTendencyFlag BiasCount BiasSources BiasFlag FlagCount AnyFlag FlagLabel
#> TRUE 0 0 FALSE 1 TRUE central
#> TRUE 0 0 FALSE 1 TRUE central
#> .AbsEstimate
#> 0.196
#> 0.191
#>
#> Settings
#> Setting Value
#> facet Rater
#> facet_source inferred
#> severity_warn 1
#> misfit_warn 1.5
#> central_tendency_max 0.25
#> bias_count_warn 1
#> bias_abs_t_warn 2
#> bias_abs_size_warn 0.5
#> bias_p_max 0.05
#> bias_source_bundles 0
#>
#> Notes
#> - Dashboard constructed successfully.