CVcindex {dynpred}

Calculate cross-validated c-index

Description

This function calculates cross-validated versions of Harrell's c-index.

Usage

CVcindex(formula, data, type = "single", matrix = FALSE)

Arguments

formula

Formula for prediction model to be used as in coxph

data

Data set in which to interpret the formula

type

One of "single", "pair" or "fullpairs". For "single" (default), the prognostic index Z_i is replaced by Z_i,(-i), for "pair", two assessments of concordance are made for each pair (i,j), one using Z_i,(-i) and Z_j,(-i), the other using Z_i,(-j) and Z_j,(-j), for "fullpairs", each of the possible pairs is left out and comparison is based on Z_i,(-i,-j) and Z_j,(-i,-j)

matrix

if TRUE, the matrix of cross-validated prognostic indices is also returned; default is FALSE

Value

A list with elements

concordant

The number of concordant pairs

total

The total number of pairs that can be evaluated

cindex

The cross-validated c-index

matrix

Matrix of cross-validated prognostic indices (only if argument matrix is TRUE

and with attribute "type" as given as input.

Author(s)

Hein Putter [e-mail]

References

Harrell FE, Lee KL & Mark DB (1996), Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors, Statistics in Medicine 15, 361-387.

van Houwelingen HC, Putter H (2012). Dynamic Prediction in Clinical Survival Analysis. Chapman & Hall.

Examples

data(ova)
# Real thing takes a long time, so on a smaller data set
ova2 <- ova[1:100,]
# Actual c-index
cindex(Surv(tyears,d) ~ Karn + Broders + FIGO + Ascites + Diam, data = ova2)
# Cross-validated c-indices
CVcindex(Surv(tyears,d) ~ Karn + Broders + FIGO + Ascites + Diam, data = ova2)
CVcindex(Surv(tyears,d) ~ Karn + Broders + FIGO + Ascites + Diam, data = ova2,
         type="pair")

CVcindex(Surv(tyears,d) ~ Karn + Broders + FIGO + Ascites + Diam, data = ova2,
         type="fullpairs")