Plot conditional Person scores from a testlet model

Usage

# S3 method for class 'mfrm_testlet_scores'
plot(
  x,
  draw = TRUE,
  style = c("interval", "precision", "distribution"),
  sort = c("input", "estimate", "uncertainty"),
  palette = c("accessible", "mono"),
  title = NULL,
  caption = NULL,
  show_title = TRUE,
  show_notes = TRUE,
  show_labels = TRUE,
  reference = 0,
  text_scale = 1,
  point_size = 2.5,
  ...
)

Arguments

x: A result from predict.mfrm_testlet().
draw: FALSE returns plot data without opening a device.
style: "interval" keeps every labeled row; "precision" plots estimates against interval width (upper minus lower bound); "distribution" shows the empirical cumulative distribution of finite point estimates, excluding prior-only and unavailable scores. No density is reconstructed.
sort: Row order for interval plots: input order, increasing estimate, or increasing interval width. Missing values come last; ties retain input order. Sorting is descriptive, not a test of differences.
palette: "accessible" uses blue and dark orange with filled/open symbols; "mono" uses dark grey with the same symbol distinctions.
title, caption: NULL uses the default text; a string replaces it; "" removes it. Interpretation notes remain in the saved plot data.
show_title, show_notes: Show the title and caption, respectively. FALSE hides text without deleting its metadata.
show_labels: Show IDs on interval and precision plots. Distribution plots summarize estimates and do not label individual IDs. For crowded precision plots use FALSE and consult the retained table.
reference: Vertical reference line in logits; NULL omits it. This is an orientation aid, not a quality threshold.
text_scale: Positive multiplier for text size.
point_size: Positive point size in ggplot millimetres; base graphics use the corresponding relative size (2.5 is the default).
...: Unused.

Value

Invisibly, an mfrm_plot_data object retaining all requested Persons, their statuses, interval endpoints and settings; use plot_data().

Details

In the default interval view, empty rows remain labeled. Open circles mark prior-only results; filled points are response-based conditional scores. The intervals exclude calibration-estimation uncertainty and are not tests of Person differences. as_ggplot() preserves all labeled rows, prior-only symbols and the conditional-interval note. plot_data() retains statuses and reasons for custom graphics or table export; conversion does not rerun scoring.

Choosing a view

Interval plots answer where estimates lie and how uncertain they are. Precision plots help identify estimates with wider intervals; width is neither a fit statistic nor a reliability coefficient. Finite intervals are required and excluded rows remain in display_data with reasons. Distribution plots summarize the selected point estimates, which are affected by shrinkage and the selected roster. They do not estimate the latent population distribution, show posterior densities, or imply independent observations.

Accessible and reusable output

Colours are supplemented by point shapes; open circles mean prior only. Use palette = "mono" for monochrome reproduction. plot_data() retains the complete source table, display_data with inclusion reasons, alt_text, interpretation notes, and display settings. Supply the text alternative and table alongside exported figures; image files alone do not automatically expose that information to screen readers. as_ggplot() preserves the view and display controls, supplies labs(alt = ...), and allows further labs(), theme() and scale edits. Rendering does not fit, score or resample. Use the same controls through plot(results, type = "scores", style = "precision").