Graph to determine whether we should add a new predictor to the model already containing other predictors. The residuals from the model is regressed on the new predictor and if the plot shows non random pattern, you should consider adding the new predictor to the model.

## Arguments

- model
An object of class

`lm`

.- variable
New predictor to be added to the

`model`

.- print_plot
logical; if

`TRUE`

, prints the plot else returns a plot object.

## Examples

```
model <- lm(mpg ~ disp + hp + wt, data = mtcars)
ols_plot_resid_regressor(model, 'drat')
```