Plot RSM/PCM threshold ladders with disorder highlighting

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 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. The number of affected groups is returned in the notes, outside the figure.
preset: Visual preset ("standard", "publication", "compact", or "monochrome").
draw: If TRUE, print the plot. Otherwise return it without drawing.

Value

A ggplot object. Use plot_data(p, "data") to access the Group, Step, StepOwner, StepIndex, Threshold, and Disordered columns for each ladder row.

Interpreting output

Each ladder shows centered step offsets for one step-owner level, including when GPCM slopes belong to a different facet. Slopes do not duplicate the threshold families. Disorder describes point estimates; inspect owner-level counts, curves and the rubric before considering category changes. Missing steps remain unavailable and are not bridged by connecting lines. No intervals or full ability-axis crossings are calculated. Save the result of plot() to retain its model context and interpretation notes. Use plot_data() for custom graphics or as_ggplot() to redraw a saved plot payload. The saved rating_scale_table() threshold view is also available as a separate plot route.

Session plot defaults

See mfrmr_visual_diagnostics for options(mfrmr.plot_preset), argument precedence, and appearance when saving or reusing a plot.

Migration in 0.2.4

This renderer is internal. Use the corresponding plot() route in mfrmr_plot_migration; the former exported name is no longer available.

Examples

# Supplementary workflow: run explicitly to keep routine checks brief.
# example("plot_threshold_ladder", run.dontrun = TRUE)
if (FALSE) { # \dontrun{
toy <- load_mfrmr_data("example_operational")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score",
                method = "MML", quad_points = 7, maxit = 30)
p <- plot(fit, type = "thresholds", draw = FALSE)
head(plot_data(p, "data"))
} # }