Statistical package for social sciences 20

Variance analyses were done using the General Linear Model procedure of the Statistical Package for Social Sciences 20.0 (SPSS Inc., Chicago, IL, USA) as a completely randomized design. The significant differences among different treatment means were separated using the Duncan’s new multiple range test at P ≤ 0.05.

Statistical analysis was performed using Statistical Package for Social Sciences 20.0 (SPSS Inc., Chicago, Illinois, USA). To test the normality of data one sample Kolmogorov-Smirnov test was used. Differences between independent samples were analyzed by Kruskal-Wallis test, while differences between paired samples were analyzed by Related samples Wilcoxon signed-rank test. P values less than 0.05 were considered statistically significant.

EpiData software (version 2.3) was used to enter the data obtained into the database, and the Statistical Package for Social Sciences 20.0 (SPSS Inc., Chicago, IL, USA) was used for the descriptive statistics. The measurement data were expressed as the numerical mean and standard deviation. Count data are expressed as percentages (%).

An analysis of variance was performed using the General Linear Model procedure of the Statistical Package for Social Sciences 20.0 (SPSS Inc., Chicago, IL, USA) in a completely randomized design. The differences among all the treatment means were identified using the Tukey’s range test at levels of significance P ≤ 0.05.

Statistical analysis was performed using the Statistical Package for Social Sciences 20.0 (SPSS Inc., Chicago, Il). Descriptive statistics were used to describe patient characteristics and immunohistochemistry scores of early-stage and advanced-stage patients. For normally distributed continuous variables, independent samples t-tests were used, whereas for not normally distributed continuous variables, Mann-Whitney tests were used. For categorical variables, chi-square tests were used.
To determine the correlation coefficients between MMP and EMT parameters, Spearman’s rho correlation coefficients were calculated; a value of .1 being considered small, .3 medium and .5 large.
A logistic regression was performed with complete or incomplete debulking as the outcome parameter and MMP-14 and EMT parameters as independent variables.

Quantitative variables were described as mean and standard deviation for symmetric distribution or median and interquartile range for asymmetric distribution. We used Pearson’s chi-square test to compare categorical variables and Mann–Whitney U test to symmetric and asymmetric distribution. A P < 0.05 was considered statistical significance. The collected data were analyzed with the Statistical Package for Social Sciences 20.0 (SPSS, Inc., Chicago, Ill).