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Error bars indicate 95%% confidence intervals Table 4 Friedman test with Dunn's multiple comparison test Friedman test P value <0.0001 Friedman statistic 36.21 Dunn's multiple comparison test Difference in rank sum Significant?

Statistical analyses were performed using the chi-square test, paired t-test, Pearson's correlation coefficient, the Mann–Whitney test, Friedman's test and Wilcoxon's rank-sum test.

There was a negligible difference in MD for the grasping (603.9 ms) vs. reaching (604.8 ms) actions, a difference that was nonsignificant (χ2 = 1; p = .317) in a non-parametric test (Friedman test) suitable for the small sample size.

In a second step, means were analyzed with the Wilcoxon-Wilcox test (Friedman analysis).

When assumptions were not valid, non-parametric tests were performed (Mann Whitney test, Friedman ANOVA).

Student's T-test, the Wilcoxon test, Friedman test and the analysis of variance (ANOVA) were used when appropriate.

Changes between measurements were assessed with nonparametric tests including Friedman test and KS test.

Data were analysed using paired T-test, Friedman test (a non-parametric test that ranks differences in responses of individual donors to different stimuli (NOMV), taking into account the variability often observed with human donors), or Fishers Exact Test (responders versus non-responders) using GraphPad Prism software.

The not normally distributed log transformed counts were compared using non-parametric tests (Friedman and Mann-Whitney rank sum test where appropriate using SPSS software version 12.0).

Differences in time to perform oral hygiene and differences in grades were analyzed using medians (with interquartile ranges (IQR)) and non-parametric tests (Kruskal-Wallis tests, Friedman tests and Wilcoxon tests).

In cases where the distribution was not Gaussian, nonparametric tests (Friedman test with Dunn's post-test for more than two events, and Wilcoxon matched pairs test for two events).