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Summarize an mfrm_bias object in a user-friendly format

Source: R/api-methods.R
summary.mfrm_bias.Rd

Summarize an mfrm_bias object in a user-friendly format

Usage

# S3 method for class 'mfrm_bias'
summary(object, digits = 3, top_n = 10, p_cut = 0.05, ...)

Arguments

object

Output from estimate_bias().

digits

Number of digits for printed numeric values.

top_n

Number of strongest bias rows to keep.

p_cut

Significance cutoff used for counting flagged rows.

...

Reserved for generic compatibility.

Value

An object of class summary.mfrm_bias with:

  • overview: interaction facets/order, cell counts, and effect-size profile

  • chi_sq: fixed-effect chi-square block

  • final_iteration: end-of-iteration status row

  • top_rows: highest-|t| interaction rows

  • notes: short interpretation notes

Details

This method returns a compact interaction-bias summary:

  • interaction facets/order and analyzed cell counts

  • effect-size profile (|bias| mean/max, significant cell count)

  • fixed-effect chi-square block

  • iteration-end convergence indicators

  • top rows ranked by absolute t

Interpreting output

  • overview: interaction order, analyzed cells, and effect-size profile.

  • chi_sq: fixed-effect test block.

  • final_iteration: end-of-loop status from the bias routine.

  • top_rows: strongest bias contrasts by |t|.

Typical workflow

  1. Estimate interactions with estimate_bias().

  2. Check summary(bias) for screen-positive and unstable cells.

  3. Use bias_interaction_report() or plot_bias_interaction() for details.

See also

estimate_bias(), bias_interaction_report()

Examples

toy <- load_mfrmr_data("example_bias")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score", method = "JML", maxit = 25)
diag <- diagnose_mfrm(fit, residual_pca = "none")
bias <- estimate_bias(fit, diag, facet_a = "Rater", facet_b = "Criterion", max_iter = 2)
summary(bias)
#> Many-Facet Rasch Bias Summary
#>   Interaction facets: Rater x Criterion | Cells: 16
#>   Order: 2 | Mode: pairwise
#>   Mean |Bias|: 0.31 | Max |Bias|: 1.103 | Screen-positive (p <= 0.050): 0
#> 
#> Fixed-effect chi-square
#>  FixedChiSq FixedDF FixedProb InferenceTier SupportsFormalInference
#>          NA      15        NA     screening                   FALSE
#>  FormalInferenceEligible PrimaryReportingEligible   ReportingUse
#>                    FALSE                    FALSE screening_only
#>                                 TestBasis InteractionFacets InteractionOrder
#>  conditional plug-in heterogeneity screen Rater x Criterion                2
#>  InteractionMode
#>         pairwise
#> 
#> Final iteration status
#>  Iteration MaxScoreResidual MaxScoreResidualPct MaxScoreResidualCategories
#>          2                0                  NA                         NA
#>  MaxLogitChange BiasCells
#>               0         0
#> 
#> Top |t| bias rows
#>                Pair Rater    Criterion Bias Size S.E.  t Prob. Obs-Exp Average
#>      R01 | Accuracy   R01     Accuracy     0.776   NA NA    NA              NA
#>       R01 | Content   R01      Content    -0.278   NA NA    NA              NA
#>      R01 | Language   R01     Language    -0.184   NA NA    NA              NA
#>  R01 | Organization   R01 Organization    -0.363   NA NA    NA              NA
#>      R02 | Accuracy   R02     Accuracy     0.246   NA NA    NA              NA
#>       R02 | Content   R02      Content    -0.031   NA NA    NA              NA
#>      R02 | Language   R02     Language    -0.209   NA NA    NA              NA
#>  R02 | Organization   R02 Organization    -0.023   NA NA    NA              NA
#>      R03 | Accuracy   R03     Accuracy    -0.055   NA NA    NA              NA
#>       R03 | Content   R03      Content     0.246   NA NA    NA              NA
#>  AbsT
#>    NA
#>    NA
#>    NA
#>    NA
#>    NA
#>    NA
#>    NA
#>    NA
#>    NA
#>    NA
#> 
#> Notes
#>  - No immediate warnings from bias summary.