`calculate_vimp`

estimates the reduction in (population) $R^2$ from
removing a particular moderator from a model containing all moderators.

```
calculate_vimp(
full_data,
weight_col,
pseudo_outcome,
...,
.VIMP_cfg,
.Model_cfg
)
```

## Arguments

- full_data
dataframe

- weight_col
Unquoted name of the weight column.

- pseudo_outcome
Unquoted name of the pseudo-outcome.

- ...
Unquoted names of covariates to include in the joint effect model.
The variable importance will be calculated for each of these covariates.

- .VIMP_cfg
A `VIMP_cfg`

object defining how VIMP should be estimated.

- .Model_cfg
A `Model_cfg`

object defining how the joint effect model should be estimated.

## References

Williamson, B. D., Gilbert, P. B., Carone, M., & Simon, N. (2021).
Nonparametric variable importance assessment using machine learning techniques.
Biometrics, 77(1), 9-22.

Williamson, B. D., Gilbert, P. B., Simon, N. R., & Carone, M. (2021).
A general framework for inference on algorithm-agnostic variable importance.
Journal of the American Statistical Association, 1-14.