Given the small sample size and non-normal distribution of the data, non-parametric Mann–Whitney
U tests were used to address research questions. Statistical analyses were run using the
R statistical software (RStudio Team 2015). A Holm–Bonferroni correction was applied to reduce the familywise error rate for multiple comparisons [
26]. This correction uses a sequential method for rejecting null hypotheses. Following Mann–Whitney
U tests,
p values were ranked from smallest to largest and compared to significance levels
α/
n,
α/(
n − 1), …
α/1, where
α was the target alpha level and
n was the total number of tests performed. Using this method for the three planned contrasts of the tongue, the test with the lowest
p value was compared to a significant level of
α = 0.05/3 = 0.016, the test with the second lowest
p value was compared to a significance level of
α = 0.05/(3 − 1) = 0.025, and the final
p value was compared to significance levels of
α = 0.05. For the two planned contrasts of the jaw, the test with the lowest
p value was compared to a significant level of
α = 0.05/2 = 0.025 and the final test was compared to a significance level of
α = 0.05. Between-group differences in lingual coordination were determined using a single Mann–Whitney
U test on lag times derived from a cross-correlation analysis. This method provides robust protection against Type I errors while maintaining higher power than a classic Bonferroni correction [
26].