### this demo runs on {compareC} version 1.3.1
library(compareC)

demo(testC)


> library(compareC)
> demo(testC)


        demo(testC)
        ---- ~~~~~

Type  <Return>   to start : 

> set.seed(2014)

> ### empirical type I error rate
> 
> rej.perc = numeric(2000)

> for (i in 1:2000) {
+ nn = 100
+ lifetimes <- rexp(nn, rate = exp(1))
+ censtimes <- rexp(nn, rate = 0.1)
+ x1 <- rnorm(nn, lifetimes)
+ x2 <- rnorm(nn, lifetimes)
+ ztimes <- pmin(lifetimes, censtimes)
+ status <- as.numeric(censtimes > lifetimes)
+ 
+ rej.perc[i] = compareC(ztimes, status, x1, x2)$pval
+ }

> mean(rej.perc < 0.05)   ### 0.0465
[1] 0.0465

> compareC(ztimes, status, x1, x2)   ### syntax to compare two Cs
$est.c
      Cxy       Cxz 
0.6245145 0.6059560 

$est.diff_c
[1] 0.01855848

$est.vardiff_c
[1] 0.002196048

$est.varCxy
[1] 0.001106914

$est.varCxz
[1] 0.001136308

$est.cov
[1] 2.358688e-05

$zscore
[1] 0.396024

$pval
[1] 0.6920874