Hello!
I am currently working on a big data set. There are different subjects
that have been measured in about 40 different variables (in this case a
measure of brain metabolism). Now I want to look at possbile significant
correlations between those variables. As some of the variables are not
normally distributed I used "spearman" as method in the function
rcor.test from the ltm-package. Unfourtunatly this results in more than
50 warnings like this due to ties:
In cor.test.default(mat[, index[i, 1]], mat[, index[i, ... :
Cannot compute exact p-value with ties
I have now two question:
1. Is there any way to calculate a exact p-value for data that is not
noramlly distributed?
2. Do have to correct for multiple comparisons in this case as I am
practically testing each possible pair of the 40 variables?
Many thanks for your help!
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