cal.cindex {GAGAs}

compute C index for a Cox model

Description

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

Usage

cal.cindex(pred, y, weights = rep(1, nrow(y)))

Arguments

pred

Predictions from a "cox" object

y

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

weights

optional observation weights

Details

Computes the concordance index, taking into account censoring. This file fully references the Cindex.R file in glmnet package.

Value

Harrel's C index

Author(s)

Trevor Hastie <[e-mail]>

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 = GAGAs(x, y, family = "cox")
pred = predict(fit, newx = x)
cat("\n Cindex:", cal.cindex(pred, y))