Plot method for multicollinearity checks — plot.see_check

The plot() method for the performance::check_collinearity() function.

Usage

# S3 method for class 'see_check_collinearity'
plot(
  x,
  data = NULL,
  theme = NULL,
  colors = c("#3aaf85", "#1b6ca8", "#cd201f"),
  size_point = 3.5,
  size_line = 0.8,
  size_title = 12,
  size_axis_title = base_size,
  base_size = 10,
  ...
)

Arguments

x: An object.
data: The original data used to create this object. Can be a statistical model.
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.
size_point: Numeric specifying size of point-geoms.
size_line: Numeric value specifying size of line geoms. linewidth is an alias for size_line.
base_size, size_axis_title, size_title: Numeric value specifying size of axis and plot titles.
...: Arguments passed to or from other methods.

Value

A ggplot2-object.

Details

If a term with a VIF below 2 has an upper confidence limit that is infinite or above the top of the plot, the plot has a caption. The caption says that the interval formula fails near VIF = 1, and that this is not high collinearity.

Examples

library(performance)
m <- lm(mpg ~ wt + cyl + gear + disp, data = mtcars)
result <- check_collinearity(m)
result
#> # Check for Multicollinearity
#> 
#> Low Correlation
#> 
#>  Term  VIF    VIF 95% CI adj. VIF Tolerance Tolerance 95% CI
#>  gear 1.53 [1.04,  2.06]     1.24      0.65     [0.48, 0.96]
#> 
#> Moderate Correlation
#> 
#>  Term  VIF    VIF 95% CI adj. VIF Tolerance Tolerance 95% CI
#>    wt 5.05 [2.57,  7.07]     2.25      0.20     [0.14, 0.39]
#>   cyl 5.41 [2.74,  7.58]     2.33      0.18     [0.13, 0.36]
#>  disp 9.97 [4.90, 13.93]     3.16      0.10     [0.07, 0.20]
plot(result)