Build an auto-filled MFRM reporting checklist

Usage

reporting_checklist(
  fit,
  diagnostics = NULL,
  bias_results = NULL,
  include_references = TRUE
)

Arguments

fit: Output from fit_mfrm().
diagnostics: Optional output from diagnose_mfrm(). When NULL, diagnostics are computed with residual_pca = "none".
bias_results: Optional output from estimate_bias() or a named list of such outputs.
include_references: If TRUE, include a compact reference table in the returned bundle.

Value

A named list with checklist tables. Class: mfrm_reporting_checklist.

Details

This helper ports the app-level reporting checklist into a package-native bundle. It does not try to judge substantive reporting quality; instead, it checks whether the fitted object and related diagnostics contain the evidence typically reported in MFRM write-ups.

Checklist items are grouped into seven sections:

Method section
Global fit
Facet-level statistics
Element-level statistics
Rating scale diagnostics
Bias/interaction analysis
Visual displays

The output is designed for manuscript preparation, audit trails, and reproducible reporting workflows.

What this checklist means

reporting_checklist() is a content-availability contract. It tells you which reporting elements are already present in the current analysis objects and which still need to be generated or documented. The primary draft-status column is DraftReady; ReadyForAPA is retained as a backward-compatible alias.

What this checklist does not justify

It is not a single run-level pass/fail decision for publication.
DraftReady = TRUE / ReadyForAPA = TRUE does not certify formal inferential adequacy.
Missing bias rows may simply mean bias_results were not supplied.

Interpreting output

checklist: one row per reporting item with Available = TRUE/FALSE. DraftReady = TRUE means the item can be drafted into a report with the package's documented caveats. ReadyForAPA is a backward-compatible alias of the same flag; neither field certifies formal inferential adequacy.
section_summary: available items by section.
references: core background references when requested.

Recommended next step

Review the rows with Available = FALSE or DraftReady = FALSE, then add the missing diagnostics, bias results, or narrative context before calling build_apa_outputs() for draft text generation.

Typical workflow

Fit with fit_mfrm().
Compute diagnostics with diagnose_mfrm().
Run reporting_checklist() to see which reporting elements are already available from the current analysis objects.

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 = "both")
chk <- reporting_checklist(fit, diagnostics = diag)
summary(chk)
#> mfrmr Reporting Checklist Summary 
#>   Class: mfrm_reporting_checklist
#>   Components (5): checklist, summary, section_summary, references, settings
#> 
#> Checklist coverage
#>                      Section Items Available DraftReady ReadyForAPA Missing
#>  Bias / Interaction Analysis     2         0          0           0       2
#>     Element-Level Statistics     4         4          2           2       0
#>       Facet-Level Statistics     3         3          1           1       0
#>                   Global Fit     2         2          2           2       0
#>               Method Section     5         5          5           5       0
#>     Rating Scale Diagnostics     4         4          4           4       0
#>              Visual Displays     2         2          2           2       0
#>  NeedsDraftWork NeedsAction
#>               2           2
#>               2           2
#>               2           2
#>               0           0
#>               0           0
#>               0           0
#>               0           0
#> 
#> Settings
#>               Setting       Value
#>    include_references        TRUE
#>  diagnostics_supplied        TRUE
#>     bias_result_count           0
#>      bias_error_count           0
#>        precision_tier exploratory
#> 
#> Notes
#>  - Summary table and preview rows were extracted.
apa <- build_apa_outputs(fit, diag)
head(chk$checklist[, c("Section", "Item", "DraftReady", "NextAction")])
#>          Section                   Item DraftReady
#> 1 Method Section    Model specification       TRUE
#> 2 Method Section       Data description       TRUE
#> 3 Method Section        Precision basis       TRUE
#> 4 Method Section            Convergence       TRUE
#> 5 Method Section  Connectivity assessed       TRUE
#> 6     Global Fit Standardized residuals       TRUE
#>                                                                                           NextAction
#> 1              Available; adapt this evidence into the manuscript draft after methodological review.
#> 2              Available; adapt this evidence into the manuscript draft after methodological review.
#> 3 Report the precision tier explicitly and keep the exploratory/hybrid caution in the APA narrative.
#> 4              Available; adapt this evidence into the manuscript draft after methodological review.
#> 5                     Document the connectivity result before making common-scale or linking claims.
#> 6    Use standardized residuals as screening diagnostics, not as standalone proof of model adequacy.
nchar(apa$report_text)
#> [1] 2420