survcomp (version 1.22.0)

concordance.index: Function to compute the concordance index for survival or binary class prediction

Description

Function to compute the concordance index for a risk prediction, i.e. the probability that, for a pair of randomly chosen comparable samples, the sample with the higher risk prediction will experience an event before the other sample or belongs to a higher binary class.

Usage

concordance.index(x, surv.time, surv.event, cl, weights, comppairs=10, strat, alpha = 0.05, outx = TRUE, method = c("conservative", "noether", "nam"), alternative = c("two.sided", "less", "greater"), na.rm = FALSE)

Arguments

x

a vector of risk predictions.

surv.time

a vector of event times.

surv.event

a vector of event occurence indicators.

cl

a vector of binary class indicators.

weights

weight of each sample.

comppairs

threshold for compairable patients.

strat

stratification indicator.

alpha

apha level to compute confidence interval.

outx

set to TRUE to not count pairs of observations tied on x as a relevant pair. This results in a Goodman-Kruskal gamma type rank correlation.

method

can take the value conservative, noether or name (see paper Pencina et al. for details).

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" (concordance index is greater than 0.5) or "less" (concordance index is less than 0.5). You can specify just the initial letter.

na.rm

TRUE if missing values should be removed.

Value

c.index

concordance index estimate.

se

standard error of the estimate.

lower

lower bound for the confidence interval.

upper

upper bound for the confidence interval.

p.value

p-value for the statistical test if the estimate if different from 0.5.

n

number of samples used for the estimation.

data

list of data used to compute the index (x, surv.time and surv.event, or cl).

comppairs

number of compairable pairs.

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.

Pencina, M. J. and D'Agostino, R. B. (2004) "Overall C as a measure of discrimination in survival analysis: model specific population value and confidence interval estimation", Statistics in Medicine, 23, pages 2109--2123, 2004.

See Also

rcorr.cens, phcpe, coxphCPE

Examples

set.seed(12345)
age <- rnorm(100, 50, 10)
sex <- sample(0:1, 100, replace=TRUE)
stime <- rexp(100)
cens   <- runif(100,.5,2)
sevent  <- as.numeric(stime <= cens)
stime <- pmin(stime, cens)
strat <- sample(1:3, 100, replace=TRUE)
weight <- runif(100, min=0, max=1)
comppairs <- 10
cat("survival prediction:\n")
concordance.index(x=age, surv.time=stime, surv.event=sevent, strat=strat,
  weights=weight, method="noether", comppairs=comppairs)
cat("binary class prediction:\n")
## is age predictive of sex?
concordance.index(x=age, cl=sex, strat=strat, method="noether")