category_curves_report: Build a category curve export bundle (preferred alias)

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

Build a category curve export bundle (preferred alias)

Description

Build a category curve export bundle (preferred alias)

Usage

category_curves_report(
  fit,
  theta_range = c(-6, 6),
  theta_points = 241,
  digits = 4,
  include_fixed = FALSE,
  fixed_max_rows = 400
)

Arguments

fit	Output from fit_mfrm().
theta_range	Theta/logit range for curve coordinates.
theta_points	Number of points on the theta grid.
digits	Rounding digits for numeric graph output.
include_fixed	If TRUE, include a legacy-compatible fixed-width text block.
fixed_max_rows	Maximum rows shown in fixed-width graph tables.

Details

Preferred high-level API for category-probability curve exports. Returns tidy curve coordinates and summary metadata for quick plotting/report integration without calling low-level helpers directly.

Value

A named list with category-curve components. Class: mfrm_category_curves.

Interpreting output

Use this report to inspect:

• where each category has highest probability across theta

• whether adjacent categories cross in expected order

• whether probability bands look compressed (often sparse categories)

Recommended read order:

1. summary(out) for compact diagnostics.

2. out$curve_points (or equivalent curve table) for downstream graphics.

3. plot(out) for a default visual check.

Typical workflow

1. Fit model with fit_mfrm().

2. Run category_curves_report() with suitable theta_points.

3. Use summary() and plot(); export tables for manuscripts/dashboard use.

See Also

category_structure_report(), rating_scale_table(), plot.mfrm_fit(), mfrmr_reports_and_tables, mfrmr_visual_diagnostics

Examples

toy <- load_mfrmr_data("example_core")
fit <- fit_mfrm(toy, "Person", c("Rater", "Criterion"), "Score", method = "JML", maxit = 25)
out <- category_curves_report(fit, theta_points = 101)
summary(out)
names(out)
p_cc <- plot(out, draw = FALSE)
class(p_cc)

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