compareCstat is an R package that compares the C-statistics (concordance statistics) between two fitted survival models (e.g., Cox models) using bootstrap resampling. It returns bootstrapped confidence intervals and a p-value for the difference in C-statistics — useful for model performance comparison.
You can install the development version of compareCstat from GitHub with:
# install.packages("devtools")
devtools::install_github("Lemonade0924/compareCstat")This is a basic example which shows you how to solve a common problem:
library(compareCstat)
library(survival)
lung <- survival::lung
# Make sure 0 = censored, 1 = event for Uno C
lung$status <- ifelse(lung$status == 2, 1, 0)
model1 <- coxph(Surv(time, status) ~ age, data = lung)
model2 <- coxph(Surv(time, status) ~ age + sex, data = lung)
compare_c_stat(model1, model2, data = lung, R = 100, method = "Uno", tau = 1 * 365.25)
#> Model C_Statistic CI_Lower CI_Upper P_Value
#> 1 Model 1 (Raw) 0.5486 0.5010 0.5962 <NA>
#> 2 Model 2 (Extended) 0.5991 0.5519 0.6463 <NA>
#> 3 Difference 0.0505 0.0099 0.0910 0.015