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Summarize a DIF/bias screening simulation

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

Summarize a DIF/bias screening simulation

Usage

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

Arguments

object

Output from evaluate_mfrm_signal_detection().

digits

Number of digits used when printing numeric summaries.

...

Reserved for generic compatibility.

Value

An object of class summary.mfrm_signal_detection with:

  • overview: run-level overview

  • detection_summary: full-precision rates by design, with design-variable aliases when applicable. DIF*, DIFClass* and BiasScreen* columns retain Planned, Available, Unavailable, Positive, MCLower, MCUpper, AllTrialsLower and AllTrialsUpper for target outcomes. Monte Carlo bounds are exact 95% binomial intervals conditional on availability; all-trial bounds describe unresolved outcomes, not confidence intervals. DIFNonTarget*/BiasNonTarget* retain summed Planned and Available cell counts and AvailableReps, the number of trials contributing a non-target proportion. Those proportions receive equal weight across contributing trials, even with unequal cell counts; their MCSE is the sample SD of the proportions divided by the square root of AvailableReps. TargetContrastAvailable, TargetContrastAbsAvailable, TargetBiasAvailable and TargetBiasTAvailable are denominators for the corresponding finite point summaries. All-missing means return NA.

  • ademp: simulation-study metadata carried forward from the original object

  • facet_names: public facet labels carried from the simulation specification

  • design_variable_aliases: accepted public aliases for design variables

  • design_descriptor: role-based design-variable metadata

  • planning_scope: explicit record of the current planning contract

  • planning_constraints: explicit record of mutable/locked design variables

  • planning_schema: structured planning metadata

  • structural_design_review: deterministic structural review of the named-facet design grid; it reports design bookkeeping rather than signal-detection performance

  • gpcm_boundary: GPCM caveat row when present

  • notes: short interpretation notes, including the bias-side screening caveat

See also

evaluate_mfrm_signal_detection(), plot.mfrm_signal_detection

Examples

# Supplementary workflow: run explicitly to keep routine checks brief.
# example("summary.mfrm_signal_detection", 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-signal-detection.rds",
  package = "mfrmr", mustWork = TRUE))
# Inspect saved$generation_warnings and the result's run/status tables.
sig_eval <- saved$result
summary(sig_eval)
} # }