dynamic-survival-metrics: Dynamic survival metrics

In yardstick: Tidy Characterizations of Model Performance

Dynamic survival metrics

Description

Dynamic survival metrics evaluate time-dependent survival predictions, producing one metric value per evaluation time point. These metrics assess predicted survival probabilities at specific time points.

Input requirements

• truth: a survival::Surv() object

• ...: list column of data frames containing .eval_time, .pred_survival, and .weight_censored columns

Available metrics

brier_survival()

Direction: minimize. Range: [0, 1]

roc_auc_survival()

Direction: maximize. Range: [0, 1]

See Also

integrated-survival-metrics for integrated survival metrics

static-survival-metrics for static survival metrics

linear-pred-survival-metrics for linear predictor survival metrics

vignette("metric-types") for an overview of all metric types

Examples

library(dplyr)
data("lung_surv")

head(lung_surv)

lung_surv |>
  brier_survival(truth = surv_obj, .pred)

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