Spss ver 22

The means and standard deviations of experimental data were calculated and analyzed with the Kruskal-Wallis test, Mann-Whitney U test, and χ² test. A 2 × 2 table was tabulated to determine the sensitivity, specificity, and positive and negative predictive values. The χ² test involved 2 × 2 tables, as well. The nonparametric Kruskal-Wallis Test was used in the evaluation of 3 categorical variables. The Mann-Whitney U test was used for the binary comparison between the 3 endoscopic techniques.
All P-values reported are 2-tailed and P < .05 was set as the level of significance. Statistical analyses were performed with SPSS Ver. 22.0 software (IBM Japan, Ltd., Tokyo, Japan).

The concordance rates of the MyHPV chip and HC2 were evaluated using the kappa coefficient (κ) with 95% confidence intervals (CIs). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the MyHPV chip and HC2 for ≥ HSILs were determined using standard statistical tests. The age-adjusted odds ratios (ORs) for ≥ HSILs with 95% CI were evaluated for different categories of MyHPV chip and HC2 results with a binary logistic regression using the SPSS ver. 22.0 software (IBM Co., Armonk, NY, USA). To analyze the MyHPV chip results, patients with single or multiple samples positive for 15 HR genotypes were categorized as HR-HPV (+). Patients with HPV-16 (+) and/or HPV-18 (+) were categorized as HPV-16/18 (+), irrespective of the presence of any other HPV genotypes. Patients with HPV-16 (–) and HPV-18 (–), 13 other HR-HPV (+) with or without low-risk HPV (+) or “HPV-other types” (+) were categorized as non-16/18 HR-HPV (+). Patients with low-risk HPV (+), “HPVother types” (+) or HPV (–) were categorized as HR-HPV (-). In cases of multiple infections, patients were classified based on the HPV genotypes associated with a higher risk of invasive cancer. For example, a patient with HPV-16 (+) and HPV-31 (+) was allocated to the HPV-16/18 (+) group.

The demographic and clinical characteristics of the ADHD and HC groups were compared using independent t-tests for continuous variables and chi-square or Fisher’s exact tests for categorical variables. Due to the predominance of boys in the ADHD group, we compared the measures between the ADHD group and HC group in boys, separately using Mann-Whitney test. We applied Spearman’s correlation analysis to investigate the correlations between ADHD clinical variables and the variables measured using the RAKMA as well as the correlation between the RAKMA stimulus–response variables and the movement variables. All statistical analyses were performed using SPSS ver. 22.0 software (IBM Corp., Armonk, NY, USA), and a p-value<0.05 was considered significant.