Spss 10

The results were reported as the mean ± standard derivation (SD) of at least three measurements. The analysis of MDA data was performed with the SPSS 10.0 statistical package (IBM, USA), while simple linear regression was performed in Excel (Microsoft, Redmond, WA, USA). Results with P values less than 0.05 were considered significant.

Paired t-tests were used to evaluate the difference between pre- and post-surgery data. Independent t-tests were used to evaluate the mean differences in SV values in the X and Y axes, as well as differences in LNG and ENV between the CI and control groups. Differences were considered statistically significant when the P value was <.05. Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS 10.0, International Business Machines Corporation, Xi’an Shaanxi, P.R. China).

All data are presented as the mean ± SE unless otherwise noted. Statistically significant differences (p < 0.05) were determined by one-way ANOVA followed by Duncan’s multiple range test using the SPSS 10.0 software package (IBM Corp., Armonk, NY, United States).

All statistical calculations were performed with SPSS 10.0 software package (IBM, Connecticut Ave NW, USA). The data set was assessed for normality using the Shapiro-Wilk test. Basic descriptive statistics (mean ± standard deviation) were calculated for all variables. Student’s t test was used to compare the between-group differences. Spearman’s rank correlation coefficients were calculated to determine the association between BMI and average and peak plantar pressure. Correlations were interpreted in accordance with the following scale of magnitude: 0.2 very weak correlation, 0.2–0.4 weak correlation, 0.4–06 moderate correlation, 0.6–0.8 strong correlation, 0.8–0.9 very strong correlation, and 0.9–1.0 indicates a perfect correlation. The level of significance was set to 0.05 for all procedures [23 ].

SPSS 10.0 (IBM, USA) was used for all analyses. Results are reported as means±SD. One-way analysis of variance was used to compare group means followed by least significant difference (LSD) t-tests for pair-wise comparisons. A P<0.05 was considered to be statistically significant.

Data are expressed as the mean ± SEM of the indicated number of independent experiments. Student’s t-test and one-way anova were used to determine significance, with P < 0.05 considered significant. The Kaplan–Meier method was used for survival analysis with a log-rank of P < 0.05 to determine significance. Statistical analyses were performed with SPSS 10.0 (IBM SPSS Statistics company, Chicago, IL, USA) for Macintosh.

All data were analyzed using Graphpad 8.0 (GraphPad Software Inc., San Diego, CA, USA) and SPSS 10.0 (IBM, Armonk, NY, USA). Continuous variables are presented as mean ± standard deviation and between-group differences were assessed using the Wilcox. test. P values < 0.05 were considered indicative of statistical significance.