Log-rank test for internal calibration and external calibration results

Usage

logrank_test(object)

Arguments

object: An object returned by calibrate or calibrate_external.

Examples

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 <- fit_lasso(
  x, survival::Surv(time, event),
  nfolds = 5, rule = "lambda.1se", seed = 11
)

# Internal calibration
cal.int <- calibrate(
  x, time, event,
  model.type = "lasso",
  alpha = 1, lambda = fit$lambda,
  method = "cv", nfolds = 5,
  pred.at = 365 * 9, ngroup = 3
)
#> Start fold 1 
#> Start fold 2 
#> Start fold 3 
#> Start fold 4 
#> Start fold 5 

logrank_test(cal.int)
#> Call:
#> survdiff(formula = formula("Surv(time, event) ~ grp"))
#> 
#> n=999, 1 observation deleted due to missingness.
#> 
#>         N Observed Expected (O-E)^2/E (O-E)^2/V
#> grp=1 333      117     68.2      34.9     50.14
#> grp=2 333       67     77.4       1.4      2.12
#> grp=3 333       42     80.4      18.3     28.52
#> 
#>  Chisq= 54.8  on 2 degrees of freedom, p= 1e-12 

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

logrank_test(cal.ext)
#> Call:
#> survdiff(formula = formula("Surv(time, event) ~ grp"))
#> 
#> n=999, 1 observation deleted due to missingness.
#> 
#>         N Observed Expected (O-E)^2/E (O-E)^2/V
#> grp=1 333       81     45.2     28.45     41.29
#> grp=2 333       39     49.6      2.27      3.44
#> grp=3 333       26     51.2     12.43     19.16
#> 
#>  Chisq= 43.2  on 2 degrees of freedom, p= 4e-10