plot.see_check_model: Plot method for checking model assumptions

In see: Model Visualisation Toolbox for 'easystats' and 'ggplot2'

Plot method for checking model assumptions

Description

The plot() method for the performance::check_model() function. Diagnostic plots for regression models.

Usage

## S3 method for class 'see_check_model'
plot(
  x,
  theme = NULL,
  colors = NULL,
  type = c("density", "discrete_dots", "discrete_interval", "discrete_both"),
  n_columns = 2,
  ...
)

Arguments

x	An object.
theme	A ggplot2-theme function, e.g. theme = theme_lucid() or theme = ggplot2::theme_dark().
colors	Character vector of length two, indicating the colors (in hex-format) for points and line.
type	Plot type for the posterior predictive checks plot. Can be "density" (default), "discrete_dots", "discrete_interval" or "discrete_both" (the ⁠discrete_*⁠ options are appropriate for models with discrete - binary, integer or ordinal etc. - outcomes).
n_columns	Number of columns to align plots.
...	Arguments passed to or from other methods.

Details

Larger models (with many observations) may take a longer time to render. Thus, the number of data points is limited to 2000 by default. Use ⁠plot(check_model(), maximum_dots = <number>)⁠ (or ⁠check_model(maximum_dots = <number>)⁠) to define the number of data points that should be shown in the plots.

Value

A ggplot2-object.

See Also

See also the vignette about check_model().

Examples

library(performance)

model <- lm(qsec ~ drat + wt, data = mtcars)
plot(check_model(model))

see documentation built on Jan. 30, 2026, 5:08 p.m.