hdnom (version 5.0)

hdnom.logrank: Log-Rank Test for Internal Calibration and External Calibration Results

Description

Log-Rank Test for Internal Calibration and External Calibration Results

Usage

hdnom.logrank(object)

Arguments

object

An object returned by hdnom.calibrate or hdnom.external.calibrate.

Examples

# NOT RUN {
library("survival")

# Load imputed SMART data
data("smart")

# Use the first 1000 samples as training data
# (the data used for internal validation)
x = as.matrix(smart[, -c(1, 2)])[1:1000, ]
time = smart$TEVENT[1:1000]
event = smart$EVENT[1:1000]

# Take the next 1000 samples as external calibration data
# In practice, usually use data collected in other studies
x_new = as.matrix(smart[, -c(1, 2)])[1001:2000, ]
time_new = smart$TEVENT[1001:2000]
event_new = smart$EVENT[1001:2000]

# Fit Cox model with lasso penalty
fit = hdcox.lasso(
  x, Surv(time, event),
  nfolds = 5, rule = "lambda.1se", seed = 11)

# Internal calibration
cal.int = hdnom.calibrate(
  x, time, event, model.type = "lasso",
  alpha = 1, lambda = fit$lasso_best_lambda,
  method = "cv", nfolds = 5,
  pred.at = 365 * 9, ngroup = 3)

hdnom.logrank(cal.int)

# External calibration
cal.ext = hdnom.external.calibrate(
  fit, x, time, event,
  x_new, time_new, event_new,
  pred.at = 365 * 5, ngroup = 3)

hdnom.logrank(cal.ext)
# }