R/ols-dsresid-vs-pred-plot.R
ols_plot_resid_stud_fit.RdPlot for detecting violation of assumptions about residuals such as non-linearity, constant variances and outliers. It can also be used to examine model fit.
ols_plot_resid_stud_fit(model, print_plot = TRUE)
| model | An object of class |
|---|---|
| print_plot | logical; if |
ols_plot_resid_stud_fit returns a list containing the
following components:
a tibble with observation number, fitted values and deleted studentized
residuals that exceed the threshold for classifying observations as
outliers/influential observations
threshold for classifying an observation as an outlier/influential observation
Studentized deleted residuals (or externally studentized residuals) is the deleted residual divided by its estimated standard deviation. Studentized residuals are going to be more effective for detecting outlying Y observations than standardized residuals. If an observation has an externally studentized residual that is larger than 2 (in absolute value) we can call it an outlier.
ols_dsrvsp_plot() has been deprecated. Instead use ols_plot_resid_stud_fit().
[ols_plot_resid_lev()], [ols_plot_resid_stand()], [ols_plot_resid_stud()]