plot.bmm_sdt_latent: Plot the latent decision-variable distributions of an SDT...

In bmm: Easy and Accessible Bayesian Measurement Models Using 'brms'

Plot the latent decision-variable distributions of an SDT model

Description

Draws the model-implied noise and signal evidence densities on the latent decision axis. For sdt_yn()/sdt_rating() the response criterion or the K-1 confidence thresholds are added as dashed vertical lines with a shaded credible band; when several boundaries are shown together (e.g. base-rate criteria or the rating thresholds) they are colour-coded. sdt_mafc() and sdt_ranking() have no boundary; with show_competitors = TRUE in latent_sdt() the max-of-distractors densities are overlaid as dashed lines, one per set size. Distinct d/sdratio conditions are faceted.

Usage

## S3 method for class 'bmm_sdt_latent'
plot(x, condition_col = NULL, line_alpha = 0.9, ...)

Arguments

x	A "bmm_sdt_latent" object from latent_sdt().
condition_col	Optional character. Condition column(s) for faceting. If NULL (default), all condition columns are used.
line_alpha	Numeric. Opacity of the criterion/threshold lines (default 0.9).
...	Ignored.

Value

A ggplot2 object.

See Also

latent_sdt(), roc_sdt()

bmm documentation built on Oct. 16, 2026, 9:08 a.m.