one way is:
x <- matrix(c(10,20,30,40,0,
10,10,10,10,50,
30,30,30,5,5), nrow=3, ncol=5, byrow=TRUE,
dimnames = list(1:3, letters[1:5])
)
ind <- combn(ncol(x), 2)
out <- apply(ind, 2, function (i) as.numeric(x[, i[1]] >= x[, i[2]]))
colnames(out) <- apply(ind, 2, function (i, nams)
paste(nams[i[1]], nams[i[2]], sep = ""), nams = colnames(x))
out
I hope it helps.
Best,
Dimitris
Iuri Gavronski wrote:
Hi,
I need to convert a ranking dataset (actually, it is an ipsative
scale) to paired-comparisons.
For example, if I have this data:
x <- matrix(c(10,20,30,40,0,
10,10,10,10,50,
30,30,30,5,5), nrow=3, ncol=5, byrow=TRUE,
dimnames = list(1:3, letters[1:5])
)
For every pair of data, I would need to apply a transformation like:
if a < b, ab = 0, otherwise ab=1
In the end, I need a matrix like that:
ab ac ad ae bc bd be cd ce de
0 0 0 1 0 0 1 0 1 1
1 1 1 0 1 1 0 1 0 0
1 1 1 1 1 1 1 1 1 1
Would anyone suggest a "no loops" way for doing that?
By the way, I would need to apply a tetrachoric correlation to this
output matrix. Should I use package polycor? Any thoughts would be
welcome.
Thanks,
Iuri.
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--
Dimitris Rizopoulos
Assistant Professor
Department of Biostatistics
Erasmus Medical Center
Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands
Tel: +31/(0)10/7043478
Fax: +31/(0)10/7043014
______________________________________________
R-help@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
