Somers' Dxy Rank Correlation
Computes Somers' Dxy rank correlation between a variable x and a
binary (0-1) variable y, and the corresponding receiver operating
characteristic curve area c. Note that Dxy = 2(c-0.5).
somers allows for a weights variable, which specifies frequencies
to associate with each observation.
somers2(x, y, weights=NULL, normwt=FALSE, na.rm=TRUE)
x |
typically a predictor variable. |
y |
a numeric outcome variable coded |
weights |
a numeric vector of observation weights (usually frequencies). Omit or specify a zero-length vector to do an unweighted analysis. |
normwt |
set to |
na.rm |
set to |
The rcorr.cens function, which although slower than somers2 for large
sample sizes, can also be used to obtain Dxy for non-censored binary
y, and it has the advantage of computing the standard deviation of
the correlation index.
a vector with the named elements C, Dxy, n (number of non-missing
pairs), and Missing. Uses the formula
C = (mean(rank(x)[y == 1]) - (n1 + 1)/2)/(n - n1), where n1 is the
frequency of y=1.
Frank Harrell
Department of Biostatistics
Vanderbilt University School of Medicine
fh@fharrell.com
set.seed(1) predicted <- runif(200) dead <- sample(0:1, 200, TRUE) roc.area <- somers2(predicted, dead)["C"] # Check weights x <- 1:6 y <- c(0,0,1,0,1,1) f <- c(3,2,2,3,2,1) somers2(x, y) somers2(rep(x, f), rep(y, f)) somers2(x, y, f)
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