facets_fit_df_guide: Guide FACETS-style fit df and ZSTD standardization

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

Guide FACETS-style fit df and ZSTD standardization

Description

facets_fit_df_guide() gives a compact user-facing guide to the degrees of freedom and ZSTD standardization choices used when comparing mfrmr fit output with FACETS-style fit tables.

Usage

facets_fit_df_guide(include_references = TRUE)

Arguments

include_references

If TRUE, include source-reference rows for the FACETS/Winsteps documentation and Rasch measurement texts that motivate the guide.

Details

The guide separates mean-square size from ZSTD standardization. Infit and outfit MnSq values answer how large the residual noise or predictability signal is. ZSTD values standardize those MnSq values using a degrees-of- freedom convention and a Wilson-Hilferty-style transformation, so ZSTD can differ even when the underlying MnSq values are nearly identical.

Two boundaries sit upstream of any df comparison. First, the residual basis: method = "MML" fits evaluate residuals at shrunken EAP person measures, whereas FACETS evaluates them at JMLE estimates, so MnSq values themselves can differ before any standardization is applied; refit with method = "JML" when the comparison requires a JMLE-style residual basis. Second, small df: mfrmr returns NA ZSTD when df < 1 because the Wilson-Hilferty transformation is numerically unstable there, while FACETS/Winsteps under WHEXACT can continue with a linear approximation, so sparse cells can show NA against a finite external value without indicating a fit difference.

Value

A bundle of class mfrm_facets_fit_df_guide with:

• summary: one-row scope summary

• formula_guide: formulas and package columns

• column_guide: where engine and FACETS-style columns appear

• decision_guide: recommended comparison steps

• interpretation_guide: how to read common difference patterns

• references: optional source-reference rows

• settings: guide metadata

See Also

diagnose_mfrm(), fit_measures_table(), facets_fit_review()

Examples

facets_fit_df_guide()
facets_fit_df_guide()$decision_guide

mfrmr documentation built on June 13, 2026, 1:07 a.m.