rcorr.cens {Hmisc} | R Documentation |
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.
rcorr.cens(x, S, outx=FALSE)
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.
|
a vector with the following named elements:
C Index
, Dxy
, S.D.
, n
, missing
,
uncensored
, Relevant Pairs
, Concordant
, and
Uncertain
n |
number of observations not missing on any input variables |
missing |
number of observations missing on x or S |
relevant |
number of pairs of non-missing observations for which
S could be ordered |
concordant |
number of relevant pairs for which x and S
are concordant. |
uncertain |
number of pairs of non-missing observations for which
censoring prevents classification of concordance of x and
S . |
Frank Harrell
Department of Biostatistics
Vanderbilt University
f.harrell@vanderbilt.edu
Newson R: Confidence intervals for rank statistics: Somers' D and extensions. Stata Journal 6:309-334; 2006.
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))