royston_survival: Royston-Sauerbei D statistic

In yardstick: Tidy Characterizations of Model Performance

Royston-Sauerbei D statistic

Description

Compute the Royston-Sauerbei D statistic

Usage

royston_survival(data, ...)

## S3 method for class 'data.frame'
royston_survival(data, truth, estimate, na_rm = TRUE, case_weights = NULL, ...)

royston_survival_vec(truth, estimate, na_rm = TRUE, case_weights = NULL, ...)

Arguments

data	A data.frame containing the columns specified by truth and ....
...	Not currently used.
truth	The column identifier for the true survival result (that is created using survival::Surv().). This should be an unquoted column name although this argument is passed by expression and supports quasiquotation (you can unquote column names). For ⁠_vec()⁠ functions, an survival::Surv() object.
estimate	The column identifier for the predicted linear predictor, this should be a numeric variable. This should be an unquoted column name although this argument is passed by expression and supports quasiquotation (you can unquote column names). For ⁠_vec()⁠ functions, a numeric vector.
na_rm	A logical value indicating whether NA values should be stripped before the computation proceeds.
case_weights	The optional column identifier for case weights. This should be an unquoted column name that evaluates to a numeric column in data. For ⁠_vec()⁠ functions, a numeric vector, hardhat::importance_weights(), or hardhat::frequency_weights().

Details

Royston D statistic is a metric that should be maximized. The output ranges from 0 to 1, with 1 indicating perfect prognostic separation.

Royston and Sauerbrei proposed $R^2_D$ as a measure of explained variation on the log relative hazard scale based on the authors’ D statistic. D measures prognostic separation of survival curves, and is closely related to the standard deviation of the prognostic index.

Larger values of the score are associated with better model performance.

Value

A tibble with columns .metric, .estimator, and .estimate and 1 row of values.

For grouped data frames, the number of rows returned will be the same as the number of groups.

For royston_survival_vec(), a single numeric value (or NA).

Author(s)

Hannah Frick

References

Royston, P., Sauerbrei, W., "A new measure of prognostic separation in survival data", Statistics in Medicine, 23, 723-748, 2004.

See Also

All linear predictor survival metrics

Examples

royston_survival(
  data = lung_surv,
  truth = surv_obj,
  estimate = .pred_linear_pred
)

yardstick documentation built on April 8, 2026, 1:06 a.m.