Spss statistical 23

The IBM SPSS statistical 23.0 software was used for the analyses. The probability plots, histograms, and the Kolmogorov-Smirnov or Shapiro-Wilk’s test of normality analyzed whether the numerical data were normally distributed. The results were presented as mean and standard deviation (SD) or median and minimum-maximum for continuous variables; number (n) and percentage (%) were given for categorical variables. The Kruskal–Wallis analysis was performed to compare headache intensity according to the level of neck disability (mild, moderate, severe, and complete). Statistical significance was accepted as p < 0.05 and The Bonferroni adjustment was used for the p value (0.05/4). The power analysis of the study was performed using the one-way ANOVA test. Alpha was 0.05, the effect size f-value was calculated as 0.37 and the power was found to be 0.97. Then, since the Kruskal–Wallis test is a non-parametric test, as suggested in the article by Prajapati et al., the Asymptotic Relative Efficiency (ARE) coefficient was multiplied by the power value found in the ANOVA test (0.955), and the power of the study for the Kruskal–Wallis test was found to be 0.926. The sample size (n = 142) was sufficient [23 ].

The OP waveforms and response amplitudes were analyzed offline. Frequency analyses were performed after high-pass 100 Hz digital filtering was applied to the recorded traces. The Fast Fourier Transform was calculated by the Labchart^® software for each 100 Hz filtered recording trace. Data of the peak power density (μV²/Hz) from different animal groups were averaged. Data are reported as mean and SD (standard deviation). Normality of the data was verified by Kolmogórov–Smirnov test. Statistical significance was assessed with Student’s t-test analyses by IBM SPSS statistical 23.0 package (SPSS Inc., Chicago, IL, USA) for paired responses. p values of less than 0.05 were considered statistically significant.