Jmp pro software version

All statistical analyses were performed with JMP® Pro software version 15.0.0 (SAS institute Inc., Cary, NC, USA). The Shapiro-Wilk test was used to determine the distribution of continuous data. Normally distributed variables were expressed as mean ± standard deviation (SD). Non-normally distributed variables were expressed as median (interquartile range [IQR]). To determine the association between two variables, Pearson correlation was used for normal distribution data, while Spearman rank correlation was used for non-normally distributed data. The Wilcoxon signed-rank test was used to compare the difference in non-normally distributed continuous variables between the two groups. The difference with p value < 0.05 was considered statistically significant.

Statistical analysis was performed using JMP Pro software version 15.0.0 (SAS Institute Inc., Cary, NC, USA). We used the Mann–Whitney U test followed by the Kruskal–Wallis rank sum test to compare BCVA, CCT, corneal sensitivity, and ECD at all measurement points (preoperatively, and 6, 12, and 24 months after DMEK). Evaluations performed with IVCM for total nerve length, number of trunks, and number of DCs were analyzed in the control group as well as in the four aforementioned groups. The correlation between the total nerve length and each endpoint (CCT, ECD, Trunk, Branch, DCs) was analyzed. The sample size was validated with calculated power of > 99%. Statistical significance was defined as p < 0.05. All quantitative variables are expressed as the mean ± standard deviation (SD).

Statistical analysis was performed using JMP Pro software version 17.1.0 (SAS Institute, Cary, NC, USA). Qualitative data were compared using the Fisher’s exact test. The Wilcoxon t-test was used for nonparametric numerical data. The Bonferroni correction is used when several dependent or independent statistical tests are being performed simultaneously. Univariate linear regression analyses were performed to determine the associations of the percentage change in the polyp area and treatment outcome. One-way analysis of variance was used to compare the BCVA and CRT before and after treatment. P < 0.05 was considered significant.

Statistical analysis was performed using the JMP Pro software version 14.0.0 (SAS Institute, Cary, NC, USA). To compare the continuous variables in each group, we used the t-test; to compare the nominal variables, we applied Pearson’s chi-squared test. Pearson correlation analysis was used for the univariable analyses. Associations between the factors and ECD loss rates at 12 months were examined using multivariable regression analysis and second-order polynomial regression after stepwise variable selection (using the minimum Bayesian information criterion and increasing the number of variables). To exclude potential multicollinearity factors between the variables, we checked the variance inflation factor. The statistical significance level was set at P-values of < 0.05.

Statistical analysis was performed using JMP Pro software version 11.2.0 (SAS Institute, Cary, NC). A two-sided paired t-test was performed to compare the changes of BCVA and CRT at baseline and at 12 months. Associations between baseline factors, cytokine concentrations, and visual and anatomical outcomes were examined with Pearson’s correlation coefficient after a normal distribution was confirmed with Shapiro-Wilk’s W-test or Spearman’s rho for categorical variables. Stepwise variable selection (using minimum Bayesian information criterion, increasing the number of variables) was performed using baseline BCVA, BCVA change at 12 months, number of ranibizumab injections, and CRT and CCT (at baseline and change at 2 months) as response variables, and disease type, disease duration (months), sex, age, axial length (mm), PVD, GLD (μm), CRT (μm), CCT (μm), BCVA, and each log concentration of aqueous humour proteins as predictor variables. The concentrations of aqueous humour proteins were log-transformed because of the lognormal distribution of these variables. To select the predictor variables in multiple regression analysis, we used the non-fixed stepwise method due to its objectivity and to avoid the risk of multicollinearity [22 ]. We then used multiple regression analysis after stepwise variable selection. P < 0.05 was considered to be significant.

Survival curves are estimated for each group in a study considered separately using the Kaplan-Meier method. The association between the aforementioned prognostic indicators and OS rates was investigated using the log-rank test and Cox proportional hazards regression analysis. The preoperative indicators observed to be statistically significant (P < 0.05) in univariate analysis were subjected to multivariate Cox proportional hazards regression analysis. A P value < 0.05 was considered statistically significant. All statistical analyses were performed using the JMP Pro software, version 13.2.0 (SAS Institute Inc., Cary, NC).