Spss statistics 26.0 for windows

The relationship between participants’ characteristics and their degree of social participation was analyzed using t-tests or chi-square tests. To identify the factors relevant to social participation, binomial logistic regression analysis (forced entry method) was conducted with social participation as the objective variable. Since mobility and the need for care were highly related, the need for care was not entered into the logistic regression analysis. SPSS Statistics 26.0 for Windows was used for all statistical analyses, with a significance level set at < 5%.

Statistical analysis of the data was performed using the SPSS Statistics 26.0 for Windows (SPSS Inc., Chicago, IL, USA). The consistency between two ophthalmologists was evaluated using the Kappa coefficient, and the sensitivity and specificity of AI automatic grading were calculated regarding the results from ophthalmologists as the gold standard. The number of referrals confirmed by AI and the ophthalmologists was calculated and compared.

IBM SPSS Statistics 26.0 for Windows was used. The results were displayed as mean ± SEM. To obtain meaningful results, media ± 2SD was used to perform the statistical evaluation of the effect of chalcone derivatives against the metabolic viability of tumor cell lines. The normality of the distribution of the results was confirmed by the Shapiro–Wilk test of normality, and the homogeneity of variance assumption was checked using Levene’s test. One-way Anova was conducted for the experimental cytotoxicity analysis with Bonferroni’s correction post hoc test. The differences in cytokine mRNA expression were analyzed using the Student’s t-test. Statistical significance was considered for p < 0.05.

Data are presented as mean ± standard deviation (SD). All statistical analyses were performed using SPSS statistics 26.0 for Windows (IBM Inc). All breathing variables were analyzed using a two‐way analysis of variance (ANOVA) for repeated measures with condition (LC and WC) and stage (rest, stage 1, stage 2, and stage 3). Similarly, the spirometry and respiratory muscle pressure data recorded at pre‐ and postexercise were also analyzed using two‐way ANOVA for repeated measures, including time (before and after cycling) and condition (LC and WC). When a significant interaction was found, post hoc multiple pairwise comparisons were performed with the Bonferroni correction. p values of <0.05 were considered statistical significance.

Statistical analysis was conducted with IBM SPSS Statistics 26.0 for Windows (International Business Machines, Armonk, NY, USA). Extreme values of more than three times the interquartile distance were identified using boxplots and excluded from further analysis. Normal distribution was examined with the Kolmogorov Smirnov test after the exclusion of extreme values. Analyses of variance with repeated measurements (ANOVAs) or Friedman-tests were performed to assess differences in PA with light and moderate to vigorous intensity between the three methods. If no sphericity was given, the Greenhouse–Geisser correction was used. Significant differences were examined with the Bonferroni post hoc test. As sedentariness was not assessed with the GPAQ 50+, differences in the assessment of sedentariness between the MW8 and the MM+ were examined while performing a t-test for paired samples or the Wilcoxon-Test. An alpha <0.05 was considered to be statistically significant.