Sas jmp version 11

The clinical characteristics of the groups (gastrectomy or nongastrectomy) were compared using a Chi-square test for categorical variables and a Student's t-test for continuous variables. Progression-free survival was the time interval between the treatment initiation date and the date of disease progression, relapse, or the last follow-up [15 (link)]. Overall survival was calculated from the treatment initiation date to death from any cause or the last follow-up date [15 (link)]. Both the relapse-free survival curve and the overall survival curve were created using the Kaplan-Meier method. Cox regression model was used for multivariate analyses of overall survival. Statistical analysis was carried out using SPSS version 18 for Windows (IBM Corporation, Armonk, New York) and SAS/JMP version 11 (SAS Institute Inc., Cary, NC). Data are expressed as means ± standard deviation. All statistical tests were 2-sided, and the differences were considered statistically significant at a P value less than 0.05.

The clinical characteristics of the groups (with or without adjuvant chemotherapy) were compared using a Chi square test for categorical variables and a Student’s t test for continuous variables. Relapse-free survival was the time interval between the gastrectomy date and the date of disease relapse. Overall survival was calculated from the diagnosis to date of death from any cause or the last follow-up date. Both the relapse-free survival curve and the overall survival curve were created using the Kaplan–Meier method. Statistical analysis was carried out using SPSS version 18 for Windows (IBM Corporation, Armonk, NY, USA) and SAS/JMP version 11 (SAS Institute Inc., Cary, NC, USA). Data are expressed as mean ± SD. All statistical tests were two-sided, and the differences were considered statistically significant at a P value <0.05.

All data are presented as mean ± standard deviation (SD). To compare the MTT data over time, we used a repeated measures of analysis of variance (ANOVA) followed by Dunnett’s multiple comparison. Numerical data were compared between groups with a t test or Mann–Whitney U test. Pearson’s correlation coefficient was used for correlation analyses. We used receiver operating characteristic (ROC) analysis to analyze the factors involved in insulin therapy and to calculate the sensitivity and specificity with respect to each optimal cutoff. To identify predictive risk factors for insulin therapy, we performed a multivariate logistic regression analysis and calculated odds ratios with 95% confidence interval. In this study, two-sided P < 0.05 was considered significant. All statistical analyses were performed using SAS JMP version 11 (SAS Institute Inc., Cary, NC, USA).