plot.latents_mixture_regression: Plot a mixture-of-regressions fit

In latents: Multilevel Latent Profile, Class and Transition Models

Plot a mixture-of-regressions fit

Description

A fit that classifies persons (id with class_level = "group") is a trajectory model, and draws the trajectory views of plot.latents_growth_mixture() (ggplot2): "trajectories" (the default), "individuals", "coefficients" and "classification". Any other fit draws base-graphics views: "fitted" (the default), "coefficients" and "posteriors".

Usage

## S3 method for class 'latents_mixture_regression'
plot(
  x,
  what = NULL,
  predictor = NULL,
  level = 0.95,
  main = NULL,
  subtitle = NULL,
  time = NULL,
  facet = FALSE,
  persons = 12L,
  max_persons = 120L,
  ...
)

Arguments

x	A fit from mixture_regression().
what	For a trajectory model: "trajectories" (each class's mean trajectory with its confidence band and the observed class means), "individuals", "coefficients" (estimates with intervals and p-values) or "classification" ("posteriors" is a synonym). Otherwise: "fitted" (the outcome against one numeric predictor, rows marked by modal class, each class's regression line), "coefficients" or "posteriors" (each unit's largest posterior probability, by class).
predictor	For "fitted", the numeric predictor for the horizontal axis; defaults to the first one in the formula.
level	Confidence level of intervals and bands.
main	Plot title; NULL for the default.
subtitle	For a trajectory model, the subtitle; NULL for the default.
time, facet, persons, max_persons	For a trajectory model, as in plot.latents_growth_mixture().
...	Unused.

Value

For a trajectory model, a ggplot object (raises latents_missing_package without ggplot2); otherwise x, invisibly, called for its plot.

Examples

fit <- mixture_regression(score ~ hours, data = study_hours, n_classes = 2,
                          n_starts = 3, seed = 1)
plot(fit)
plot(fit, what = "coefficients")

latents documentation built on Oct. 16, 2026, 5:09 p.m.