rcorr.cens {Hmisc} | R Documentation

## Rank Correlation for Censored Data

### Description

Computes the `c` index and the corresponding generalization of Somers' Dxy rank correlation for a censored response variable. Also works for uncensored and binary responses, although its use of all possible pairings makes it slow for this purpose.

### Usage

    rcorr.cens(x, S, outx=FALSE)

### Arguments

`x` | a numeric predictor variable
`S` | an `Surv` object or a vector. If a vector, assumes that every observation is uncensored.
`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.

### Value

a vector with the following named elements: `C Index, Dxy, S.D., n, missing, uncensored, Relevant Pairs, Concordant`, `Uncertain`

### Author(s)

Frank Harrell
Department of Biostatistics
Vanderbilt University
f.harrell@vanderbilt.edu

### See Also

somers2

### Examples

    set.seed(1)
    x <- round(rnorm(200))
    y <- rnorm(200)
    rcorr.cens(x, y, outx=TRUE)   # can correlate non-censored variables
    if(.R.) library(survival)
    age <- rnorm(400, 50, 10)
    d.time <- rexp(400)
    cens   <- runif(400,.5,2)
    death  <- d.time <= cens
    d.time <- pmin(d.time, cens)
    rcorr.cens(age, Surv(d.time, death))

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