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mult_comp_perm_corr(dataX,dataY,n_perm,tail,alpha_level,stat,reports,seed_state)

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mult_comp_perm_corr(dataX,dataY,n_perm,tail,alpha_level,stat,reports,seed_state)

by

David Groppe (view profile)

 

04 Feb 2012 (Updated )

Permutation test of null hypothesis of no correlation between one more pairs of variables.

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Description

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.

MATLAB release MATLAB 7.8 (R2009a)
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Comments and Ratings (1)
19 Jul 2014 Right Grievous

I'm trying to test the relationship between two variables and this test seems to be exactly what I'm looking for, however, when I run the test on my data it says the familywise alpha level is 0, the p value it returns is also 0, why is this?

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Updates
17 Sep 2012 1.1

Comments updated

14 Aug 2015 1.2

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

14 Aug 2015 1.3

Minimal change to command line output.

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