plot.mfrm_signal_detection: Plot DIF/bias screening simulation results

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

Plot DIF/bias screening simulation results

Description

Plot DIF/bias screening simulation results

Usage

## S3 method for class 'mfrm_signal_detection'
plot(
  x,
  signal = c("dif", "bias"),
  metric = c("power", "false_positive", "estimate", "screen_rate",
    "screen_false_positive"),
  x_var = c("n_person", "n_rater", "n_criterion", "raters_per_person"),
  group_var = NULL,
  draw = TRUE,
  ...
)

Arguments

x	Output from evaluate_mfrm_signal_detection().
signal	Whether to plot DIF or bias screening results.
metric	Metric to plot. For signal = "bias", prefer metric = "screen_rate" for the screening hit rate. The older metric = "power" spelling is retained as a backwards-compatible alias that maps to BiasScreenRate.
x_var	Design variable used on the x-axis. When x was generated from a sim_spec with custom public facet names, the corresponding aliases (for example n_judge, n_task, judge_per_person) are also accepted. Role keywords (person, rater, criterion, assignment) are accepted as an abstraction over the current two-facet schema.
group_var	Optional design variable used for separate lines. The same alias rules as x_var apply.
draw	If TRUE, draw with base graphics; otherwise return plotting data.
...	Reserved for generic compatibility.

Value

If draw = TRUE, invisibly returns plotting data. If draw = FALSE, returns that plotting-data list directly. The returned list includes resolved canonical variables (x_var, group_var) together with public labels (x_label, group_label), design_variable_aliases, design_descriptor, planning_scope, planning_constraints, planning_schema, display_metric, and interpretation_note so callers can label bias-side plots as screening summaries rather than formal power/error-rate displays.

See Also

evaluate_mfrm_signal_detection(), summary.mfrm_signal_detection

Examples

sig_eval <- suppressWarnings(evaluate_mfrm_signal_detection(
  n_person = 8,
  n_rater = 2,
  n_criterion = 2,
  raters_per_person = 1,
  reps = 1,
  maxit = 30,
  bias_max_iter = 1,
  seed = 123
))
plot(sig_eval, signal = "dif", metric = "power", x_var = "n_person", draw = FALSE)

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