I would like to use the corr.test function from the psych package in order to calculate the correlation and the significance between corresponding columns of two dataframes.
A simplified example of the dataframes Df1 and Df2 I am working with is this:
set.seed(42)
Df1 <- data.frame(matrix(runif(50), 10, 5))
Df2 <- data.frame(matrix(runif(50), 10, 5))
Please note that this question has been already answered here:
Column by column correlation between two data sets with R?
but only for the the correlation part, i.e., it lacks the significance I am looking for, since it uses the cor function and not the corr.test one.
Any help would be greatly appreciated.
Using cor.test in mapply and subsetting desired statistics, where estimate is the correlation.
mapply(\(x, y) cor.test(x, y)[c('estimate', 'p.value')], Df1, Df2)
# X1 X2 X3 X4 X5
# estimate 0.2486405 -0.408098 0.03718413 -0.09967868 0.4662738
# p.value 0.4884952 0.2416943 0.9187721 0.7841065 0.1743502