# Deleted studentized residual vs fitted values plot

Source:`R/ols-dsresid-vs-pred-plot.R`

`ols_plot_resid_stud_fit.Rd`

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.

## Arguments

- model
An object of class

`lm`

.- threshold
Threshold for detecting outliers. Default is 2.

- print_plot
logical; if

`TRUE`

, prints the plot else returns a plot object.

## Value

`ols_plot_resid_stud_fit`

returns a list containing the
following components:

- outliers
a

`data.frame`

with observation number, fitted values and deleted studentized residuals that exceed the`threshold`

for classifying observations as outliers/influential observations- threshold
`threshold`

for classifying an observation as an outlier/influential observation

## Details

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.

## Examples

```
model <- lm(mpg ~ disp + hp + wt + qsec, data = mtcars)
ols_plot_resid_stud_fit(model)
ols_plot_resid_stud_fit(model, threshold = 3)
```