summary.mfrm_diagnostics: Summarize an 'mfrm_diagnostics' object in a user-friendly...

In mfrmr: Estimation and Diagnostics for Many-Facet Measurement Models

Summarize an mfrm_diagnostics object in a user-friendly format

Description

Summarize an mfrm_diagnostics object in a user-friendly format

Usage

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

Arguments

object	Output from diagnose_mfrm().
digits	Number of digits for printed numeric values.
top_n	Number of highest-absolute-Z fit rows to keep.
...	Reserved for generic compatibility.

Details

This method returns a compact diagnostics summary designed for quick review:

• design overview (observations, persons, facets, categories, subsets)

• global fit statistics

• approximate reliability/separation by facet

• top facet/person fit rows by absolute ZSTD

• counts of flagged diagnostics (unexpected, displacement, interactions)

Value

An object of class summary.mfrm_diagnostics with:

• overview: design-level counts and residual-PCA mode

• overall_fit: global fit block

• reliability: facet-level separation/reliability summary

• top_fit: top ⁠|ZSTD|⁠ rows

• flags: compact flag counts for major diagnostics

• notes: short interpretation notes

Interpreting output

• overview: analysis scale, subset count, and residual-PCA mode.

• overall_fit: global fit indices.

• reliability: facet separation/reliability block, including model and real bounds when available.

• top_fit: highest ⁠|ZSTD|⁠ elements for immediate inspection.

• flags: compact counts for key warning domains.

Typical workflow

1. Run diagnostics with diagnose_mfrm().

2. Review summary(diag) for major warnings.

3. Follow up with dedicated tables/plots for flagged domains.

See Also

diagnose_mfrm(), summary.mfrm_fit()

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(diag)

mfrmr documentation built on March 31, 2026, 1:06 a.m.