plot.mfrm_design_evaluation: Plot a design-simulation study

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

Plot a design-simulation study

Description

Plot a design-simulation study

Usage

## S3 method for class 'mfrm_design_evaluation'
plot(
  x,
  facet = c("Rater", "Criterion", "Person"),
  metric = c("separation", "reliability", "infit", "outfit", "misfitrate",
    "severityrmse", "severitybias", "convergencerate", "elapsedsec", "mincategorycount"),
  x_var = c("n_person", "n_rater", "n_criterion", "raters_per_person"),
  group_var = NULL,
  draw = TRUE,
  ...
)

Arguments

x	Output from evaluate_mfrm_design().
facet	Facet to visualize.
metric	Metric to plot.
x_var	Design variable used on the x-axis.
group_var	Optional design variable used for separate lines.
draw	If TRUE, draw with base graphics; otherwise return plotting data.
...	Reserved for generic compatibility.

Details

This method is designed for quick design-planning scans rather than polished publication graphics.

Useful first plots are:

• rater metric = "separation" against x_var = "n_person"

• criterion metric = "severityrmse" against x_var = "n_person" when you want aligned recovery error rather than raw location shifts

• rater metric = "convergencerate" against x_var = "raters_per_person"

Value

If draw = TRUE, invisibly returns a plotting-data list. If draw = FALSE, returns that list directly.

See Also

evaluate_mfrm_design(), summary.mfrm_design_evaluation

Examples

sim_eval <- evaluate_mfrm_design(
  n_person = c(30, 50),
  n_rater = 4,
  n_criterion = 4,
  raters_per_person = 2,
  reps = 1,
  maxit = 15,
  seed = 123
)
plot(sim_eval, facet = "Rater", metric = "separation", x_var = "n_person", draw = FALSE)

mfrmr documentation built on March 31, 2026, 1:06 a.m.