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For KM analysis, 3 of 1040 subjects were identified as being outliers by Tukey's criterion; thus, they were removed from the data analysis.
If injurious fall types were identified we further investigated the relation between these injurious fall types on the one hand and socio-demographic characteristics, perceived cause of the fall, consequences of the fall, and health-related characteristics on the other by means of chi-square (α = 0.05) and one-way ANOVA with Tukey's criterion for post-hoc pairwise comparisons (α = 0.05).
As oversensitivity of CNV detection for these individuals likely led to unrealistically high values [35], we eliminated extreme outliers, ones exceeding Tukey's criterion of the third quartile value plus three times the inter-quartile range [60].
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Multiple comparison post-hoc tests using Tukey's honestly significant difference criterion were used to investigate potential differences between individual groups.
Tukey's honestly significant difference criterion was applied as a post hoc test in case of the one-way ANOVA showing a significant main effect.
The three groups of subjects (healthy volunteers, patients with RBD and patients without RBD) were compared using a non-parametric Kruskal-Wallis test corrected for multiple comparisons using Tukey's honestly significant difference criterion.
Protected multi-comparison tests with Tukey's honestly significant difference criterion 10 after the ANOVA show a significance level of 1.0 × 10−5 for the difference of Tz between cell edge (Cell_Edge) and nucleus (Nucleus) (# in Fig. 7b) and 0.01 for the difference of Tz between Nucleus and Cyto1 (* in Fig. 7b).
To identify the specific groups that are significantly different, we used Tukey's honestly significant difference (HSD) criteria which is based on Studentized range distribution for determining critical values [ 36].
ns=non-significant; (ANOVA+ Tukey's post-hoc).
One-way ANOVA with Tukey's post test.
Mean ratios were compared using ANOVA and Tukey's test.
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