View source: R/variable_importance.R
calculate_vimp | R Documentation |
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
)
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 |
.Model_cfg |
A |
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.
calculate_linear_vimp()
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.