nsim: Number of simulations for the Durbin-Watson-Test.
Returns
Invisibly returns the p-value of the test statistics. A p-value < 0.05 indicates autocorrelated residuals.
Details
Performs a Durbin-Watson-Test to check for autocorrelated residuals. In case of autocorrelation, robust standard errors return more accurate results for the estimates, or maybe a mixed model with error term for the cluster groups should be used.
Examples
m <- lm(mpg ~ wt + cyl + gear + disp, data = mtcars)check_autocorrelation(m)
See Also
Other functions to check model assumptions and and assess model quality: check_collinearity(), check_convergence(), check_heteroscedasticity(), check_homogeneity(), check_model(), check_outliers(), check_overdispersion(), check_predictions(), check_singularity(), check_zeroinflation()