Spss statistics for window version 25

This study used descriptive statistics to analyze individual characteristics, biological function, symptoms, functional status, general health perceptions, and HRQOL using frequencies, percentages, mean, and standard deviation (SD). We performed a t-test and analyses of variance (ANOVA) to analyze differences in HRQOL according to individual characteristics. We then analyzed relationships among HRQOL and associated factors using Pearson’s correlation coefficient. Finally, we performed a multiple linear regression analysis with an Enter method to identify the factors associated with patients’ HRQOL. All significant variables based on t-test, ANOVA, and Pearson’s correlation were entered into the multiple linear regression model to control for confounding variables. For all tests, we considered a p-value < 0.05 to be statistically significant. Statistical analyses were performed using IBM SPSS Statistics for Window, Version 25.0 (Armonk, NY, USA).

The IBM-SPSS statistics for Window version 25.0 (IBM Corp., Armonk NY, USA) was used to analyse the quantitative data. One-way analysis of variance (ANOVA) and the SNK (Student–Newman–Keuls) mean comparison tests were used to assess the differences (p < 0.05) among the three strains used in this study.