CoOL_6_calibration_plot {CoOL} | R Documentation |
Calibration curve
Description
Shows the calibration curve e.i. the predicted risk vs the actual risk by subgroups.
Usage
CoOL_6_calibration_plot(
exposure_data,
outcome_data,
model,
sub_groups,
ipw = 1,
restore_par_options = TRUE
)
Arguments
exposure_data |
The exposure dataset. |
outcome_data |
The outcome vector. |
model |
The fitted non-negative neural network. |
sub_groups |
The vector with the assigned sub_group numbers. |
ipw |
a vector of weights per observation to allow for inverse probability of censoring weighting to correct for selection bias |
restore_par_options |
Restore par options. |
Value
A calibration curve.
References
Rieckmann, Dworzynski, Arras, Lapuschkin, Samek, Arah, Rod, Ekstrom. 2022. Causes of outcome learning: A causal inference-inspired machine learning approach to disentangling common combinations of potential causes of a health outcome. International Journal of Epidemiology <https://doi.org/10.1093/ije/dyac078>
Examples
#See the example under CoOL_0_working_example
[Package CoOL version 1.1.2 Index]