Import an mirt fit to an mfrmr-compatible bundle

Extracts item, step, and person parameters from a mirt::mirt() fit and returns an mfrm_imported_fit object. The returned object has the public slots summary, facets$person, facets$others, steps, config, and source that the mfrmr plot and table helpers expect. Only unidimensional Rasch and partial-credit response models with positive slopes and ordinary category scores are supported. Graded-response, guessing and multidimensional models are refused. With compute_fit = TRUE, source Infit / Outfit statistics are attached.

Usage

import_mirt_fit(
  fit,
  model = c("RSM", "PCM", "GPCM"),
  item_facet = "Item",
  compute_fit = FALSE
)

# S3 method for class 'mfrm_imported_fit'
summary(object, digits = 3L, ...)

# S3 method for class 'summary.mfrm_imported_fit'
print(x, ...)

Arguments

fit: An object returned by mirt::mirt() (a SingleGroupClass).
model: One of "RSM", "PCM", "GPCM". The importer does not reconstruct all source constraints; pass the model that was estimated. Non-unit slopes require "GPCM". A polytomous "RSM" import requires source item type "rsm".
item_facet: Name to assign to the item facet in the imported bundle (default "Item").
compute_fit: Logical. When TRUE, run mirt::itemfit() and mirt::personfit() to populate Infit / Outfit / OutfitZSTD columns on the returned facet tables, plus build a measurement-side diagnostics bundle. Person fit uses source EAP scores. Default FALSE extracts parameters without calculating fit statistics.
object, x: An imported measurement bundle.
digits: Number of digits for displayed estimates.
...: Additional arguments (unused by imported summaries).

Value

An mfrm_imported_fit object. Slots:

summary: Model / method / N / LogLik / AIC / BIC.
facets$person: Person ID, Estimate, SE, Extreme, plus Infit / Outfit / OutfitZSTD / Zh when compute_fit = TRUE.
facets$others: Item-level estimates and slopes; with compute_fit = TRUE, also available Infit / Outfit statistics.
steps: Absolute adjacent-category thresholds on the source ability scale, labelled in Parameterization; these are not centered step deviations. Rating-scale offsets are included.
config: List with the declared model and facet names used for the import; downstream plot and table helpers consult this to dispatch correctly on the imported bundle.
diagnostics: mfrm_diagnostics-shape bundle when compute_fit = TRUE; NULL otherwise.
source: Imported-from metadata.

Source scale

Item difficulty is the mean of its absolute adjacent-category thresholds. Source identification and slopes are retained without rescaling. For mirt gpcmIRT and rsm, the category offset is included as b - c / a. Person estimates are EAP; the SE column contains conditional posterior SDs, not sampling SEs. Person labels use retained source row names or P-prefixed row positions. Original identifiers discarded by mirt cannot be recovered. Imported summaries describe these conventions without assuming a native mfrmr population distribution or slope normalization.

Imported uncertainty

Imported SEs retain the source package's interpretation. The measurement-side diagnostics do not reconstruct the joint parameter covariance, so joint facet chi-square statistics, degrees of freedom and p-values are unavailable. Posterior SDs do not supply sampling SEs for separation reliability. Other separation summaries require valid SEs for every finite estimate and remain descriptive. Imported Wright maps show points only: source uncertainty conventions do not establish one common confidence-interval calculation. Re-import older saved bundles from the existing source-package fit to update difficulties, thresholds and uncertainty labels. The mirt and TAM importers accept compute_fit = TRUE when source fit statistics are needed; no model re-estimation is required.

Scope

Use summary() for source-scale tables and plot() for a point-only Wright map. Available source fit statistics remain in the facet and diagnostic tables. Native model curves, comprehensive mfrm_results() reports, response-level diagnostics, run_qc_pipeline(), bias/DIF analysis, anchoring and portable calibration are unavailable for imported bundles. This is a one-way fitted-object import of the documented fields.

Examples

# \donttest{
if (requireNamespace("mirt", quietly = TRUE)) {
  response_matrix <- matrix(sample(0:1, 120, replace = TRUE), nrow = 40)
  colnames(response_matrix) <- paste0("Item", seq_len(ncol(response_matrix)))
  fit <- mirt::mirt(response_matrix, 1, itemtype = "Rasch", verbose = FALSE)
  imported <- import_mirt_fit(fit, model = "RSM")
  imported$summary
}
#>   Model Method Source  N Persons Facets Categories    LogLik      AIC      BIC
#> 1   RSM    MML   mirt 40      40      1         NA -81.62847 171.2569 178.0125
#>   Converged ConvergenceStatus
#> 1      TRUE                ok
# }

Import an `mirt` fit to an mfrmr-compatible bundle