Generates the data needed for the calibration plot — get_calibration_plot_data

Generates the data needed for the calibration plot. The calibration plot needs to separate the model predictions by risk groups. First the function separates the predictions in n_groups then computes the mean value of the model predictions and also the observed value. The observed value is the estimated value at the study time estimated using a Kaplan-Meier estimator.

Usage

get_calibration_plot_data_surv(
  model,
  data,
  n_groups,
  type = "predictions_aggregated"
)

Arguments

model: Model generated with mv_model_cox() or mv_model_logreg(). Needs the predictions parameter of the model, to generate it the function calculate_predictions() must be executed over the model. If we want to obtain also the recalibrated data the model must be initalize the recalibrated predictions with calculate_predictions_recalibrated_type_1() and calculate_predictions_recalibrated_type_2().
data: Data for what the observed predictions will be calculated.
n_groups: Number of groups that must be calculated.
type: Type of the predictions that the calibration plot data should be generated from: "predictions_aggregated", "predictions_recal_type_1" or "predictions_recal_type_2"

Value

tibble with the data ready to generate a calibration plot.

group	prediction	observed
1	0.03	0.05
...	...	...
n_group	0.84	0.79

Examples

if (FALSE) { # \dontrun{
model |>
  get_calibration_plot_data_surv(data = test_data, n_groups = 10, type = "predictions_aggregated")
} # }