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copied!<p>I'm not sure if this addresses your problem in a proper manner, but take a look at William Revelle's <code>psych</code> package. <code>corr.test</code> returns list of matrices with correlation coefs, # of obs, t-test statistic, and p-value. I know I use it all the time (and AFAICS you're also a psychologist, so it may suite your needs as well). Writing loops is not the most elegant way of doing this.</p> <pre><code>library(psych) corr.test(mtcars) ( k <- corr.test(mtcars[1:5]) ) Call:corr.test(x = mtcars[1:5]) Correlation matrix mpg cyl disp hp drat mpg 1.00 -0.85 -0.85 -0.78 0.68 cyl -0.85 1.00 0.90 0.83 -0.70 disp -0.85 0.90 1.00 0.79 -0.71 hp -0.78 0.83 0.79 1.00 -0.45 drat 0.68 -0.70 -0.71 -0.45 1.00 Sample Size mpg cyl disp hp drat mpg 32 32 32 32 32 cyl 32 32 32 32 32 disp 32 32 32 32 32 hp 32 32 32 32 32 drat 32 32 32 32 32 Probability value mpg cyl disp hp drat mpg 0 0 0 0.00 0.00 cyl 0 0 0 0.00 0.00 disp 0 0 0 0.00 0.00 hp 0 0 0 0.00 0.01 drat 0 0 0 0.01 0.00 str(k) List of 5 $ r : num [1:5, 1:5] 1 -0.852 -0.848 -0.776 0.681 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : chr [1:5] "mpg" "cyl" "disp" "hp" ... .. ..$ : chr [1:5] "mpg" "cyl" "disp" "hp" ... $ n : num [1:5, 1:5] 32 32 32 32 32 32 32 32 32 32 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : chr [1:5] "mpg" "cyl" "disp" "hp" ... .. ..$ : chr [1:5] "mpg" "cyl" "disp" "hp" ... $ t : num [1:5, 1:5] Inf -8.92 -8.75 -6.74 5.1 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : chr [1:5] "mpg" "cyl" "disp" "hp" ... .. ..$ : chr [1:5] "mpg" "cyl" "disp" "hp" ... $ p : num [1:5, 1:5] 0.00 6.11e-10 9.38e-10 1.79e-07 1.78e-05 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : chr [1:5] "mpg" "cyl" "disp" "hp" ... .. ..$ : chr [1:5] "mpg" "cyl" "disp" "hp" ... $ Call: language corr.test(x = mtcars[1:5]) - attr(*, "class")= chr [1:2] "psych" "corr.test" </code></pre>

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