R: compute C index for a Cox model

Cindex {glmnet} | R Documentation

## compute C index for a Cox model

### Description

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

### 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.

### Author(s)

Trevor Hastie hastie@stanford.edu

### 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

    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)
    apply(pred, 2, Cindex, y=y)
    cv.glmnet(x, y, family = "cox", type.measure = "C")

[Package glmnet version 4.1-2 Index]