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Summarize a diagnostic-screening simulation study

Source: R/api-simulation.R
summary.mfrm_diagnostic_screening.Rd

Summarizes output from evaluate_mfrm_diagnostic_screening() for reporting, appendix export, and draw-free visualization handoff. The summary keeps simulation operating characteristics separate from inferential conclusions: fit, marginal, pairwise, and report-review signals are screening readouts rather than pass/fail evidence.

Usage

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

Arguments

object

Output from evaluate_mfrm_diagnostic_screening().

digits

Number of digits used in numeric summaries.

...

Reserved for generic compatibility.

Value

An object of class summary.mfrm_diagnostic_screening with:

  • overview: run-level design, replication, convergence, and report-review metadata

  • reading_order: recommended order for reading the summary tables

  • next_actions: action-oriented triage for interpreting and exporting the summary

  • reporting_notes: report-facing boundaries and recommended wording safeguards

  • figure_recipes: recommended figure/display recipes for the draw-free plot-data tables

  • scenario_summary: aggregated scenario-by-design screening summaries

  • performance_summary: operating-characteristic rates and runtime summaries

  • report_signal_summary: optional mfrm_report() readiness/review signals

  • scenario_contrast: misspecification-minus-well-specified contrasts

  • plot_*: long-form draw-free plot tables for overview, report, contrast, and runtime views

  • planning metadata, settings, ADEMP metadata, and interpretation notes

See also

evaluate_mfrm_diagnostic_screening(), plot.mfrm_diagnostic_screening, plot_data()

Examples

# Supplementary workflow: run explicitly to keep routine checks brief.
# example("summary.mfrm_diagnostic_screening", run.dontrun = TRUE)
if (FALSE) { # \dontrun{
# One saved replication illustrates output structure, not precise rates.
# Regeneration recipe: examples/simulation-results.R in the package.
saved <- readRDS(system.file("examples", "simulation-diagnostic-screening.rds",
  package = "mfrmr", mustWork = TRUE))
# Inspect saved$generation_warnings and the result's run/status tables.
diag_eval <- saved$result
summary(diag_eval)
} # }