check_heteroscedasticity {performance} | R Documentation |
Significance testing for linear regression models assumes that the model errors (or residuals) have constant variance. If this assumption is violated the p-values from the model are no longer reliable.
check_heteroscedasticity(x, ...) check_heteroskedasticity(x, ...)
x |
A model object. |
... |
Currently not used. |
This test of the hypothesis of (non-)constant error is also called Breusch-Pagan test (1979).
The p-value of the test statistics. A p-value < 0.05 indicates a non-constant variance (heteroskedasticity).
There is also a plot()
-method implemented in the see-package.
Breusch, T. S., and Pagan, A. R. (1979) A simple test for heteroscedasticity and random coefficient variation. Econometrica 47, 1287-1294.
m <<- lm(mpg ~ wt + cyl + gear + disp, data = mtcars) check_heteroscedasticity(m) # plot results if (require("see")) { x <- check_heteroscedasticity(m) plot(x) }