Spss statistics version 25.0 for mac os

The assumption of normality of all continuous variables was verified using the Kolmogorov–Smirnov test. Normally distributed variables (Kolmogorov–Smirnov test with p ≥ 0.05) were reported as mean and standard deviations (SD), and non-normally distributed variables (Kolmogorov–Smirnov test with p < 0.05) were reported as medians and interquartile ranges. The Chi-square test for categorical variables and the Student T-test for quantitative variables were performed to explore differences in clinical features between patients with and without midfoot ulcer occurrence. To select the optimal diagnostic cut-off points on the scale of radiographic analyses, ROC curves were used. This is a graphical method of representing sensitivity and specificity for a given test. In addition, for those radiographic measurements with sensitivity and specificity less than 100%, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were calculated for lateral talar-first metatarsal angle, calcaneal pitch angle, and cuboid height. p-values < 0.05 were considered statistically significant, with confidence intervals (CI) of 95%. All statistical analyses were performed using SPSS statistics version 25.0 for Mac OS (SPSS, Chicago, IL, USA).

Quantitative variables were presented as the median and interquartile range (IQR), while qualitative variables were presented as the percentage and frequencies. A Wilcoxon test for paired samples was used to explore the differences in stance subphases, stride length, velocity during gait, and comfort between different shoe conditions. The Kruskal-Wallis test was used to understand differences between foot type and changes in spatiotemporal parameters during gait. The strength of difference in the effect size was calculated using a phi coefficient for a chi-square test and an r coefficient for a non-parametric test considering the values > 0.01 as a small effect, > 0.30 as a medium effect, and > 0.50 as a large effect. Cohen’s d was calculated as the effect size for the parametric test using an effect size calculator (http://www.uccs.edu/~lbecker/) and considering the values > 0.2, > 0.5, and > 0.8 as small, moderate, and large effects, respectively [23 (link)]. All statistical analyses were performed using SPSS statistics version 25.0 for Mac OS (SPSS, Chicago, IL, USA). Furthermore, GraphPad^® for Mac OS was used to generate graphics to assess the differences between different shoe conditions and barefoot. P values < 0.05 were considered statistically significant with confidence intervals of 95%.

The assumption of normality of all continuous variables was verified using the Kolmogorov-Smirnov test. Normally distributed variables (Kolmogorov-Smirnov test with p ≥ 0 05) were reported as mean and standard deviations, and non-normally distributed variables (Kolmogorov-Smirnov test with p < 0.05) were reported as medians and interquartile ranges. A Friedman test for paired samples was used to explore the metatarsal that supports the highest plantar pressure after MHR because of the non-normal distribution of the variable. A Wilcoxon-Mann Whitney for independent samples was used to explore the relation among the highest PPP and PTI with reulceration.
All statistical analyses were performed using SPSS statistics version 25.0 for Mac OS (SPSS, Chicago, IL, USA). p values < 0.05 were considered statistically significant with a confidence interval of 95%.