Log-rank test for internal calibration and external calibration results

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=1 333 121 67.0 43.45 62.07 #> grp=2 333 63 77.3 2.63 4.01 #> grp=3 333 41 80.7 19.54 30.53 #> #> Chisq= 65.8 on 2 degrees of freedom, p= 5e-15
# 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=1 339 80 46.7 23.69 34.90 #> grp=2 327 40 48.0 1.35 2.01 #> grp=3 333 26 51.2 12.42 19.15 #> #> Chisq= 37.5 on 2 degrees of freedom, p= 7e-09