concordance.index {survcomp} | R Documentation

## 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.

### Note

The "direction" of the concordance index (< 0.5 or > 0.5) is the opposite than the rcorr.cens function in the `Hmisc` package. So you can easily get the same results than rcorr.cens by changing the sign of `x`.

### Author(s)

Benjamin Haibe-Kains, Markus Schroeder

### 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")

[Package survcomp version 1.42.0 Index]