plot_threshold_ladder: Plot RSM/PCM threshold ladders with disorder highlighting

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

Plot RSM/PCM threshold ladders with disorder highlighting

Description

Renders the Rasch-Andrich threshold structure as a vertical ladder per step-facet level. Each tick is a tau_k; lines connecting adjacent thresholds are coloured to make disordered crossings (⁠tau_{k+1} < tau_k⁠) visually obvious. For RSM there is one ladder; for PCM (and bounded GPCM) there is one ladder per step_facet level.

Usage

plot_threshold_ladder(
  fit,
  highlight_disorder = TRUE,
  preset = c("standard", "publication", "compact", "monochrome"),
  draw = TRUE
)

Arguments

fit	An mfrm_fit from fit_mfrm().
highlight_disorder	Logical. When TRUE (default), draw disordered segments with the preset's fail colour and add a subtitle counting the disordered groups.
preset	Visual preset ("standard", "publication", "compact", or "monochrome").
draw	If TRUE, draw with base graphics.

Value

An mfrm_plot_data object with a data slot containing columns Group, Step, Threshold, Disordered for each ladder row.

Interpreting output

Within each ladder, thresholds should ascend monotonically. A disordered crossing (highlighted in the fail colour) suggests that the corresponding category is rarely the most likely response over any logit interval, and is a common trigger for category-collapsing decisions.

See Also

category_structure_report(), category_curves_report(), plot.mfrm_fit() (type = "ccc").

Examples

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

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