Summarize an mfrm_fit object in a user-friendly format

Summarize an mfrm_fit object in a user-friendly format

Usage

# S3 method for class 'mfrm_fit'
summary(object, digits = 3, top_n = 5, ...)

Arguments

object: Output from fit_mfrm().
digits: Number of digits for printed numeric values.
top_n: Number of extreme facet/person rows shown in summaries.
...: Reserved for generic compatibility.

Value

An object of class summary.mfrm_fit with:

overview: global model/fit indicators
facet_overview: per-facet estimate distribution summary
person_overview: person-measure distribution summary
step_overview: threshold/step diagnostics
top_person: highest/lowest person measures
top_facet: extreme facet-level estimates
notes: short interpretation notes

Details

This method provides a compact, human-readable summary oriented to reporting. It returns a structured object and prints:

model fit overview (N, LogLik, AIC/BIC, convergence)
facet-level estimate distribution (mean/SD/range)
person measure distribution
step/threshold checks
high/low person measures and extreme facet levels

Interpreting output

overview: convergence and information criteria.
facet_overview: per-facet spread and range of estimates.
person_overview: distribution of person measures.
step_overview: threshold spread and monotonicity checks.
top_person / top_facet: extreme estimates for quick triage.

Typical workflow

Fit model with fit_mfrm().
Run summary(fit) for first-pass diagnostics.
Continue with diagnose_mfrm() for element-level fit checks.

Examples

toy <- load_mfrmr_data("example_core")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score", method = "JML", maxit = 25)
summary(fit)
#> Many-Facet Rasch Model Summary
#>   Model: RSM | Method: JMLE
#>   N: 768 | Persons: 48 | Facets: 2 | Categories: 4
#>   LogLik: -820.949 | AIC: 1755.899 | BIC: 2020.595
#>   Converged: Yes | Iterations: 67
#> 
#> Facet overview
#>      Facet Levels MeanEstimate SDEstimate MinEstimate MaxEstimate  Span
#>  Criterion      4            0      0.287      -0.414       0.248 0.663
#>      Rater      4            0      0.313      -0.329       0.334 0.662
#> 
#> Person measure distribution
#>  Persons  Mean    SD Median   Min   Max  Span
#>       48 0.001 1.101  0.082 -2.18 2.686 4.866
#> 
#> Step parameter summary
#>  Steps    Min   Max  Span Monotonic
#>      3 -1.325 1.385 2.711      TRUE
#> 
#> Most extreme facet levels (|estimate|)
#>      Facet    Level Estimate
#>  Criterion  Content   -0.414
#>      Rater      R04    0.334
#>      Rater      R02   -0.329
#>  Criterion Accuracy    0.248
#>      Rater      R01   -0.196
#> 
#> Highest person measures
#>  Person Estimate
#>    P023    2.686
#>    P024    2.203
#>    P036    1.834
#>    P002    1.676
#>    P014    1.259
#> 
#> Lowest person measures
#>  Person Estimate
#>    P015   -2.180
#>    P045   -1.823
#>    P008   -1.669
#>    P006   -1.523
#>    P026   -1.523
#> 
#> Notes
#>  - No immediate warnings from fit-level summary checks.

Summarize an `mfrm_fit` object in a user-friendly format