Calculate Variable Importance of HTEs

Source: R/variable_importance.R

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.