# Cindex

From glmnet v3.0-2
by Trevor Hastie

##### compute C index for a Cox model

Computes Harrel's C index for predictions from a `"coxnet"`

object.

- Keywords
- models, Cross-validation, Cox

##### Usage

`Cindex(pred, y, weights = rep(1, nrow(y)))`

##### Arguments

- pred
Predictions from a

`"coxnet"`

object- y
a survival response object - a matrix with two columns "time" and "status"; see documentation for "glmnet"

- weights
optional observation weights

##### Details

Computes the concordance index, taking into account censoring.

##### References

Harrel Jr, F. E. and Lee, K. L. and Mark, D. B. (1996)
*Tutorial in biostatistics: multivariable prognostic models: issues in
developing models, evaluating assumptions and adequacy, and measuring and
reducing error*, Statistics in Medicine, 15, pages 361--387.

##### See Also

`cv.glmnet`

##### Examples

```
# NOT RUN {
set.seed(10101)
N = 1000
p = 30
nzc = p/3
x = matrix(rnorm(N * p), N, p)
beta = rnorm(nzc)
fx = x[, seq(nzc)] %*% beta/3
hx = exp(fx)
ty = rexp(N, hx)
tcens = rbinom(n = N, prob = 0.3, size = 1) # censoring indicator
y = cbind(time = ty, status = 1 - tcens) # y=Surv(ty,1-tcens) with library(survival)
fit = glmnet(x, y, family = "cox")
pred = predict(fit, newx = x)
Cindex(pred, y)
cv.glmnet(x, y, family = "cox", type.measure = "C")
# }
```

*Documentation reproduced from package glmnet, version 3.0-2, License: GPL-2*

### Community examples

Looks like there are no examples yet.