Check model for (non-)constant error varianceSource:
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.
The p-value of the test statistics. A p-value < 0.05 indicates a non-constant variance (heteroskedasticity).
This test of the hypothesis of (non-)constant error is also called Breusch-Pagan test (1979).
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.
Other functions to check model assumptions and and assess model quality: