brier: Brier Score for Right-Censored Survival Data at a Fixed Time

In survdnn: Deep Neural Networks for Survival Analysis Using 'torch'

Brier Score for Right-Censored Survival Data at a Fixed Time

Description

Computes the Brier score at a fixed time point using inverse probability of censoring weights (IPCW).

Usage

brier(object, pre_sp, t_star)

Arguments

object	A 'Surv' object with observed time and status.
pre_sp	A numeric vector of predicted survival probabilities at 't_star'.
t_star	The evaluation time point.

Value

A single numeric value representing the Brier score.

Examples

library(survival)
data(veteran, package = "survival")
mod <- survdnn(Surv(time, status) ~
age + karno + celltype, data = veteran, epochs = 50, verbose = FALSE)
pred <- predict(mod, newdata = veteran, type = "survival", times = c(30, 90, 180))
y <- model.response(model.frame(mod$formula, veteran))
survdnn::brier(y, pre_sp = pred[["t=90"]], t_star = 90)

survdnn documentation built on Aug. 8, 2025, 6:05 p.m.