summary.mfrm_data_description: Summarize a data-description object

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

Summarize a data-description object

Description

Summarize a data-description object

Usage

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

Arguments

object	Output from describe_mfrm_data().
digits	Number of digits for numeric rounding.
top_n	Maximum rows shown in preview blocks.
...	Reserved for generic compatibility.

Details

This summary is intended as a compact pre-fit quality snapshot for manuscripts and analysis logs.

Value

An object of class summary.mfrm_data_description.

Interpreting output

Recommended read order:

• overview: sample size, persons/facets/categories.

• missing: missingness hotspots by selected input columns.

• score_distribution: category usage balance.

• facet_overview: coverage per facet (minimum/maximum weighted counts).

• agreement: observed-score inter-rater agreement (when available).

Very low MinWeightedN in facet_overview is a practical warning for unstable downstream facet estimates.

Typical workflow

1. Run describe_mfrm_data() on raw long-format data.

2. Inspect summary(ds) before model fitting.

3. Resolve sparse/missing issues, then run fit_mfrm().

See Also

describe_mfrm_data(), summary.mfrm_fit()

Examples

toy <- load_mfrmr_data("example_core")
ds <- describe_mfrm_data(toy, "Person", c("Rater", "Criterion"), "Score")
summary(ds)

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