Empirical values for chromosome-wise significance thresholds were determined using a permutation test.
The newly identified genes were further filtered using a permutation test.
We evaluated the level of statistical significance using a permutation test with 1000 iterations, randomly selected subjects and randomly shuffled order of the semantic coordinates across the target objects.
It should be noted that the same significant differences between ipsi- and contraversive trials were seen even after we compared the contra- versus ipsiversive conditions using a permutation test as described in the Methods section.
The significance of the difference between two obtained ROC areas was calculated using a permutation test [12].
When comparing two groups (comparisons between cultivars), a t test was used instead, in case of unequal variances p value was determined using a permutation test.
A model-free method for setting the experiment-wise Type I error rate is using a permutation test.
Analyzing samples from multiple experiments was accomplished using a permutation test, as described by Lehmann, Example 6 [41].
Using a permutation test, we found a significant association between group and recognition score (ANOVA: p = .0006).0006
This testing approach is very flexible, and could be adapted to any method searching for epistasis using a permutation test.
These were then converted to p-values using a permutation test with 1000 permutations (implying that the smallest p-value estimable is 0.001).
