Added variable plot provides information about the marginal importance of a
predictor variable, given the other predictor variables already in
the model. It shows the marginal importance of the variable in reducing the
residual variability.

ols_plot_added_variable(model)

## Arguments

model |
An object of class `lm` . |

## Details

The added variable plot was introduced by Mosteller and Tukey
(1977). It enables us to visualize the regression coefficient of a new
variable being considered to be included in a model. The plot can be
constructed for each predictor variable.

Let us assume we want to test the effect of adding/removing variable *X* from a
model. Let the response variable of the model be *Y*

Steps to construct an added variable plot:

Regress *Y* on all variables other than *X* and store the residuals (*Y* residuals).

Regress *X* on all the other variables included in the model (*X* residuals).

Construct a scatter plot of *Y* residuals and *X* residuals.

What do the *Y* and *X* residuals represent? The *Y* residuals represent the part
of **Y** not explained by all the variables other than X. The *X* residuals
represent the part of **X** not explained by other variables. The slope of the line
fitted to the points in the added variable plot is equal to the regression
coefficient when **Y** is regressed on all variables including **X**.

A strong linear relationship in the added variable plot indicates the increased
importance of the contribution of **X** to the model already containing the
other predictors.

## Deprecated Function

`ols_avplots()`

has been deprecated. Instead use `ols_plot_added_variable()`

.

## References

Chatterjee, Samprit and Hadi, Ali. Regression Analysis by Example. 5th ed. N.p.: John Wiley & Sons, 2012. Print.

Kutner, MH, Nachtscheim CJ, Neter J and Li W., 2004, Applied Linear Statistical Models (5th edition).
Chicago, IL., McGraw Hill/Irwin.

## See also

[ols_plot_resid_regressor()], [ols_plot_comp_plus_resid()]

## Examples

model <- lm(mpg ~ disp + hp + wt, data = mtcars)
ols_plot_added_variable(model)