Permutation test of null hypothesis of no correlation between one more pairs of variables.
Updated Tue, 08 Mar 2016 21:45:02 +0000

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Permutation test based on Pearson's linear correlation coefficient (r) or Spearman's rank correlation coefficient (rho). This function can perform the test on one or more pairs of variables. When applying the test to multiple pairs of variables, the "max statistic" method is used for adjusting the p-values of each variable for multiple comparisons (Groppe, Urbach, & Kutas, 2011). Like Bonferroni correction, this method adjusts p-values in a way that controls the family-wise error rate. However, the permutation method will be more powerful than Bonferroni correction when different variables in the test are correlated.

Cite As

David Groppe (2024). mult_comp_perm_corr (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2009a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes

RandStream now called correctly for most recent versions of MATLAB when seed state is needed.

Minimal change to command line output.

Now runs even if unable to set seed state (due to 2014+ version of Matlab)

Comments updated