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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 0.015These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.