Stat view se graphics

Data were expressed as mean ± standard deviation for functional data and median (range) for morphologic data. Differences between groups were analyzed using analysis of variance (ANOVA) for functional data. The ANOVA test was followed by the unpaired t-test for comparison between groups. The Mann–Whitney U test was applied for comparison between groups of morphologic data. Probability values of p < 0.05 were considered significant. Data analysis was performed using the Stat View SE Graphics program (Abacus Concepts Inc., Berkeley, CA, USA).

Group data were expressed as mean ± SD (standard deviation) for functional data or median (range) or interquartile range (IQR) for morphologic data. Differences between groups were analyzed using analysis of variance (ANOVA) for functional data. ANOVA was followed by an unpaired t-test for comparison between groups. The Kruskal–Wallis test was applied to the morphologic data followed by a Mann–Whitney U-test for comparison between groups. In vitro data were analyzed by the Mann–Whitney U test. Correlation coefficients were calculated using the Spearman rank method. Probability values of p < 0.05 were considered significant. Data analysis was performed using the Stat View SE Graphics program (Abacus Concepts Inc., Berkeley, CA-USA.

Descriptive statistics were performed to investigate the sample characteristics; mean ± standard deviation, or median and interquartile interval (IQR) were chosen to summarize continuous variables, while absolute and relative frequencies (n, %) were used for categorical variables. Differences among time points were analyzed using repeated measures analysis of variance (ANOVA) for functional data or Friedman test (corrected for missing values) for immunohistochemical data. When repeated measures ANOVA was statistically significant, the post hoc tests with Bonferroni correction were performed. The Friedman test applied for morphologic data multiple comparison was followed by the Wilcoxon rank test for comparison between time points (T0, T1, T2, T12). Paired data Student’s t-test was applied to compare days of work lost before and after BT. Data analysis was performed using the Stat View SE Graphics program (Abacus Concepts Inc., Berkeley, CA, USA) and IBM SPSS Statistics 23 for Windows (SPSS, Chicago, IL). A p value <0.05 was considered as statistically significant.

The raw data is available as S1 Table. Normally distributed data were presented as the mean and (SD) and skewed distributions as the median (25th-75th percentiles). Differences between groups were evaluated by analysis of variance (ANOVA) or Mann-Whitney´s U test, as appropriate, and differences in frequencies by contingency table analysis. Correlations between parameters were studied by simple and multiple linear regression analysis. The statistical software was StatView SE+Graphics (Abacus Concepts, NJ). P < 0.05 was considered statistically significant.

The data are shown as mean ± standard deviation (SD) for functional data and median (range) or interquartile range (IQR) for morphologic data. Differences between groups were analyzed using analysis of variance (ANOVA) for functional data, followed by the unpaired t-test for comparison between groups. The Kruskal-Wallis test followed by the Mann-Whitney U test for comparison between groups was used to compare morphologic data. Spearman rank method was used to calculate correlation coefficients. A p value less than 0.05 was considered significant. Data analysis was performed using the Stat View SE Graphics program (Abacus Concepts, Inc., Berkeley, CA, USA).

Statistical analysis was performed with the “Statview SE + Graphics”™ (Abacus Concepts Inc., Berkeley, CA) program and a Macintosh PowerBook 1400cs/117 personal computer (Apple Computer Inc., Cupertino, CA, USA). A decimal scale was used for visual acuity measurements and converted to LogMAR quotation using a conversion chart for statistical analysis. The data included the mean, standard deviation, standard error and range. The Kolmogorov-Smirnov test was used to check normality of the distribution, and a factorial ANOVA test was used for analysis. In addition, an intra-group linear regression analysis was performed. A 95% confidence interval was set up, and a P value < 0.05 was considered statistically significant.