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The permutation test recommended for testing if a correlation is zero can be used in R Suppose we have two columns of data a <- c(1,2,3) b <- c(3,6,5) the the two-sided p-value for testing of the a,b Pearson correlation equals zero is outputted using pout (assuming 1000 simulations). |
Permutation test in R for a bivariate Pearson correlation
The permutation test recommended for testing if a correlation is zero can be used in R
Suppose we have two columns of data
a <- c(1,2,3) b <- c(3,6,5)
the the two-sided p-value for testing of the a,b Pearson correlation equals zero is outputted using pout (assuming 1000 simulations).
robs <- cor(a,b) repout <- replicate(1000,cor(a,sample(b))) rout<-(abs(repout)>robs) pout<-sum(rout=="TRUE")/1000