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One of the methods utilises the vibration responses of cracked structures in time domain and is called deviation from normal distribution (DND).
Due to variation in sample size and deviation from normal distribution, non-parametric analyses were used.
We used the Kolmogorov-Smirnov procedure to test for deviation from normal distribution.
Deviation from normal distribution was tested by Kolmogorof-Smirnov-Test. 2D∶4D ratios of the subjects were analyzed by a 2 (diagnosis)×2 (sex)×2 (hand) factorial ANCOVA with repeated measurement on the factor hand and age as covariate.
The metrics comprised: a) coefficient of variation (CV) defined as the ratio of variance in the profile to the average of the profile b) kurtosis (measure of deviation from normal distribution in the profile) To compute gene expression levels, each dataset component of the integrating panel was normalized as described above (each sample divided by array average intensity).
Log transformation was performed for variables with significant deviation from normal distribution before further analyses.
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*Mean and standard deviation from normal distributions are used to approximate β and Dirichlet distributions for simulation purposes.
As normal distribution was not appropriate in a simulation because there would be a non-negligible probability of sampling an impossible value, in this case a probability below zero, we therefore used the mean and standard deviation from normal distributions to approximate β distributions for binomial data and Dirichlet distributions for multinomial data.
Values deviating more than three standard deviations from normal distribution were carefully investigated.
Deviations from normal distribution were checked with the Shapiro-Wilk and Shapiro-Francia tests for normality.
Significant deviations from normal distribution were detected for several metabolite/patient group combinations (Figures 2 and 3).
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