This is an unstable process. I suggest using the bootstrap to get a
confidence interval for the rank of each correlation coefficient among all
non-diagonal correlations.
-
Frank Harrell
Department of Biostatistics, Vanderbilt University
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Alex,
Here's one way to do it, using for() loops.
Jean
library(Hmisc)
# using Swiss Fertility and Socioeconomic Indicators (1888) Data
m <- data.matrix(swiss)
output <- rcorr(m)
varnames <- dimnames(m)[[2]]
nvar <- length(varnames)
# for loops through all possible pairs
for(i in 1:(nvar-1)) {
Hi,
i have used rcorr() for calculating pearsons r and according p-values
for my data, giving me 2 matrices.
Now I would like to print scatterplots for all results with "good"
correlation values.
So i need a way to extract the row-name and column-name for each item in
the matrix with "good" r-va
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