Plot 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_dsrvsp_plot(model)
model | An object of class |
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ols_dsrvsp_plot
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_rsdlev_plot()], [ols_srsd_plot()], [ols_srsd_chart()]
model <- lm(mpg ~ disp + hp + wt + qsec, data = mtcars) ols_dsrvsp_plot(model)