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mult_comp_perm_t2(d​ata1,data2,n_perm,t​ail,alpha_level,mu,​t_stat,reports,seed​_state)

version 1.2.0.0 (15.9 KB) by David Groppe
Independent sample t-statistic based permutation test; corrects for multiple comparisons

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Updated 15 Mar 2018

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Independent sample permutation test based one of three t-statistics (equal variance, Welch's t, t_dif). This function can perform the test on one variable or simultaneously on multiple variables. When applying the test to multiple variables, the "tmax" method is used for adjusting the p-values of each variable for multiple comparisons (Blair & Karnisky, 1993; Westfall & Young, 1993). Like Bonferroni correction, this method adjusts p-values in a way that strongly 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 (2020). mult_comp_perm_t2(data1,data2,n_perm,tail,alpha_level,mu,t_stat,reports,seed_state) (https://www.mathworks.com/matlabcentral/fileexchange/54585-mult_comp_perm_t2-data1-data2-n_perm-tail-alpha_level-mu-t_stat-reports-seed_state), MATLAB Central File Exchange. Retrieved .

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Updates

1.2.0.0

Welch's t added as a possible test statistic. This is somewhat robust to differences in variance between the groups being tested and is almost as powerful as the standard pooled variance t-statistic when variances are equal between groups.

1.1.0.0

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

MATLAB Release Compatibility
Created with R2014b
Compatible with any release
Platform Compatibility
Windows macOS Linux