compute C index for a Cox model
Computes Harrel's C index for predictions from a "coxnet" object.
Cindex(pred, y, weights = rep(1, nrow(y)))
pred |
Predictions from a |
y |
a survival response object - a matrix with two columns "time" and "status"; see documentation for "glmnet" |
weights |
optional observation weights |
Computes the concordance index, taking into account censoring.
Trevor Hastie hastie@stanford.edu
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.
cv.glmnet
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")
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