Sas 6

Data are presented as mean ± SD and analysed using SAS 6.12 software (SAS Institute, Cary, NC, USA). Comparisons among multiple groups were performed with one-way anova. Least significant difference method was used to compare between two groups. P < 0.05 was considered statistically significant.

All data were analysed by the SAS 6.12 software package. Continuous variables were expressed as mean ± standard deviation (SD), and categorical variables were expressed as percentages. The differences between men and women were calculated using the unpaired Student’s t-test for continuous data and the chi-squared (χ^{2 (link)}) test for categorical data. The differences in the distributions of genotypes and allele frequencies between male and female hypertensive subjects were evaluated by logistic regression analysis. The relationship between genotypes and BP levels was performed by multiple linear regression analysis. Considering that demographic factors may affect BP levels, the patient’s age, BMI, cigarette smoking and alcohol drinking status etc. were adjusted in the regression model. In order to investigate the combined effects of cigarette smoking, alcohol drinking and eNOS Glu298Asp polymorphism on BP, analysis of covariance (ANCOVA) was used to test the difference in SBP or DBP among different genotypes, and comparison between groups was assessed by the Student-Newman-Keuls multiple range test (SNK, q-test). A p<0.05 was considered to be statistically significant.

The results were analyzed with Statistical Analysis System (SAS) 6.12 (SAS Institute Inc., Cary, NC, USA) and are expressed as the mean ± standard deviation. To compare the differences among the groups, statistical significance was analyzed using Pearson’s χ² test and a one-way analysis of variance followed by post hoc comparisons. P<0.05 was considered to indicate a statistically significant difference.

Statistical analysis software (SAS) 6.12 was used for the statistical analysis. Statistical significance for intergroup differences was assessed by the 2-tailed Fisher’s exact test, chi-squared test for categorical variables and Student’s t-test for continuous variables. A level of P<0.05 was considered statistically significant.

All results are presented as the means ± standard deviation (SD). The BBB scores were analyzed through repeated measures analysis of variance (ANOVA). The data obtained from Prussian blue staining were analyzed with the Mann-Whitney U test. All other data were analyzed using one-way ANOVA to identify significant differences among the three groups. Statistical significance was inferred when the p value was less than 0.05. All statistical analyses were performed using the SAS 6.12 software program (SAS Institute, Cary, NC, USA).

The data are presented as mean ± standard deviation (SD) from at least three independent experiments. Statistically significant differences (p < 0.05) between the different groups were measured using a one-way analysis of variance with Tukey post hoc analysis when indicated. All statistical analysis was completed by a SAS 6.12 statistical software package (SAS, Cary, NC, USA).