plot_rater_severity_profile: Plot per-rater severity ranking with confidence interval...

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

Plot per-rater severity ranking with confidence interval whiskers

Description

Ranks the levels of a chosen rater facet by estimated severity and draws each level as a horizontal CI whisker around the point estimate. Optional gentle / strict guidance bands at ⁠+/-0.5⁠ and ⁠+/-1.0⁠ logit relative to the centred mean make rater calibration easy to read for training feedback.

Usage

plot_rater_severity_profile(
  fit,
  diagnostics = NULL,
  facet = "Rater",
  ci_level = 0.95,
  show_bands = TRUE,
  preset = c("standard", "publication", "compact", "monochrome"),
  draw = TRUE
)

Arguments

fit	An mfrm_fit from fit_mfrm().
diagnostics	Optional diagnose_mfrm() output. When omitted, diagnose_mfrm(fit, residual_pca = "none") is run internally.
facet	Facet name to plot (default "Rater"). Any non-Person facet name is accepted.
ci_level	Confidence level used for the whiskers (default 0.95). Bounds use ⁠+/- z * ModelSE⁠.
show_bands	Logical. When TRUE (default) draw shaded ⁠+/-0.5⁠ (gentle) and ⁠+/-1.0⁠ (strict) logit guidance bands.
preset	Visual preset.
draw	If TRUE, draw with base graphics.

Value

An mfrm_plot_data object whose data slot contains columns Level, Estimate, SE, CI_Lower, CI_Upper, Band.

Interpreting output

The vertical reference line at zero is the sum-to-zero centring point. Levels well within ⁠+/- 0.5 logit⁠ (gentle band) are typically interchangeable in operational scoring; levels outside ⁠+/- 1.0 logit⁠ (strict band) deserve targeted training or anchoring.

See Also

diagnose_mfrm(), analyze_facet_equivalence(), plot_facet_equivalence().

Examples

toy <- load_mfrmr_data("example_core")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score",
                method = "JML", maxit = 30)
p <- plot_rater_severity_profile(fit, draw = FALSE)
head(p$data$data)

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