Spss 21.0 for windows

The continuous variables were reported as medians and interquartile ranges (IQR), whereas the categorical variables were reported as numbers and percentages. The inter-rater agreement of the endoscopic indices was analyzed using Cohen’s weighted Kappa coefficient. Correlation analysis was performed using Spearman’s rank correlation coefficient. The comparison between the coefficients of correlations of MES and UCEIS with the FC levels was conducted using Meng’s z coefficient [28 ]. The receiver operating characteristic (ROC) curves for the FC levels were assessed to predict the clinical and endoscopic activity indices. The comparison between the area under the ROC curve was analyzed using DeLong’s test [29 (link)]. A p value of <0.05 was considered statistically significant. All statistical analyses were performed using SPSS 21.0 for Windows (IBM SPSS Statistics, Ver. 21.0; IBM Co., Armonk, NY) and R V.3.4.0 (R Development Core Team).

The data were evaluated using SPSS 21.0 for Windows (IBM, Armonk, NY, USA). Nonparametric data were compared using the Mann–Whitney U test and Kruskal–Wallis test. The numerical variability were expressed as mean ± standard deviation (SD). A p value of <0.05 was considered significant.

SPSS 21.0 for Windows (IBM Corp., Armonk, NY, USA) was used in all statistical analyses. The variables were investigated using visual (histograms, probability plots) and analytical (Kolmogorov–Smirnov test) methods to determine whether they were normally distributed. Descriptive analyses were presented using means and standard deviations for normally distributed variables and medians and interquartile range for nonnormally distributed variables. Categorical variables were presented as numbers and percentages. Student’s t-test or the Mann–Whitney U test were used to compare continuous variables, while the chi-square test and Fisher’s exact test, if necessary, were used to identify statistical differences for categorical variables. Pearson’s correlation analysis was used to assess correlations between UA and other parameters. Stepwise multivariate logistic regression analysis was done to examine the association between the functional significance of the lesions and other variables. Variables with P < 0.25 in univariate logistic regression were included in a multivariate logistic regression model. In the logistic regression model, UA level was assumed to be a binary variable according to the cutoff point detected in the receiver operating characteristic (ROC) curve analysis. P < 0.05 was defined as statistically significant.

All study results were evaluated according to the per protocol analysis. All data were analysed using SPSS 21.0 for Windows (IBM Corp., Armonk, USA). An independent t-test, x² test, and Fisher’s exact test were used for confirmation of homogeneity between the two groups at baseline. The Kolmogorov-Smirnov test and the Shapiro-Wilk test were used to check the normality of the data. For the clinical variables and the concentrations of bacteria, an independent t-test allowed a comparison between probiotic and placebo groups. Otherwise, the Mann-Whitney U test was used. A value of P ≤ 0.05 was considered statistically significant.

A one-way analysis of variance (ANOVA) with Dunnett post hoc analysis was used to compare CT attenuation in the peritoneal implant, SNR, CNR_A, CNR_B, and qualitative image parameters among VMI₄₀, VMI₅₀, IMR, and FBP images. Subgroup analysis was performed according to the region in which the peritoneal implant was located. A P value <.05 was considered to indicate statistical significance. Ratios of improvement in SNR and CNR values were compared between VMI₄₀ and conventional FBP and IMR images according to the region. Interreader variability was calculated by using weighted κ statistics and interpreted as follows: 0.21–0.40, fair; 0.41–0.60, moderate; 0.61–0.80, substantial; and 0.81–1.00, almost perfect. A commercially available software package (SPSS 21.0 for Windows; IBM, Inc, Armonk, NY) was employed for the statistical analyses.

All data were checked for normality using a Shapiro-Wilks test and were presented as mean and standard deviation (SD). The effects of hinge position on GE, kinematics (CL and CR), and EMG peak intensity for reach muscle were tested using a one-way ANOVA for repeated measures. The statistical analyses were performed using the IBM SPSS 21.0 for Windows (SPSS Inc., Chicago, IL). The level of statistical significance was set to α = 0.05 in all tests.
For the EMG-PC scores, two types of statistical analyses were conducted. Between-subject effects were determined by calculating the respective means of the 30 PC-scores obtained from the 30 cycles of each subject and each hinge position. Then the distribution of these subject means were compared between hinge conditions using the repeated measures ANOVAs. Intra-subject effects of the hinge position on the EMG-PC scores were analyzed by performing one-way ANOVAs on the 90 PC-scores obtained for each subject.