This function performs a permutation test for the null hypothesis that a sample is drawn from a symmetric distribution with a specific mean. The test is based on the t-statistic and is applicable to both single-sample and paired-sample/repeated measures t-tests. Unlike traditional parametric t-tests, this method does not assume that the data comes from a Gaussian distribution, making it more versatile. This function can test a single variable or multiple variables simultaneously. When applying the test to multiple variables, the 'tmax' method is used to adjust the p-values for multiple comparisons (Blair & Karniski, 1993). Similar to Bonferroni correction, this method adjusts p-values to control the family-wise error rate. However, when the variables tested are correlated, the permutation method is more powerful than Bonferroni correction. Reference: Blair, RC & Karniski, W. (1993). An alternative method for significance testing of waveform differences. Psychophysiology.