Results are presented as the mean ± SD. In Experiment 1, pharmacokinetic parameters were analyzed via multiple comparative tests using Bonferroni’s method. Dose dependency was analyzed using linear regression analysis. In Experiment 2, baseline characteristics were analyzed using the one-way ANOVA and Chi-square tests. In addition, MA efficacy was analyzed using the paired t test for intragroup comparisons before and after intervention and the Williams test for intergroup comparisons. SPSS Statistics ver. 25 for Windows (IBM Inc., Tokyo, Japan) and SAS ver. 9.4 for Windows (SAS Institute Inc., Cary, NC) were used for statistical analyses. For each test, a significant difference was defined as p<0.05.
Sas ver 9.4 for windows
Manufactured by SAS Institute
Sourced in United States
SAS ver. 9.4 for Windows is a software product that provides data analysis and management capabilities. It is designed to run on the Windows operating system. The software enables users to access, manipulate, and analyze data from various sources.
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Lab products found in correlation
6 protocols using sas ver 9.4 for windows
1
Pharmacokinetic and Efficacy Analysis
2
Cervical Radiculopathy T2 Relaxation Analysis
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All data are expressed as mean±standard deviation. A paired t-test was used to compare T2 values between the right and left sides for each DRG from C4 to C8 in radiculopathy patients and C5 to C8 in healthy subjects. Correlations were calculated between the T2 relaxation times or T2 ratios and clinical symptoms such as the VAS scores using Pearson product-moment correlation. Spearman’s correlation coefficients were used to test intra- and interindividual reliabilities. SAS ver. 9.4 for Windows (SAS Institute Inc., Cary, NC, USA) was used for analyses. A p<0.05 was considered statistically significant.
3
Probit Analysis of Compound Efficacy
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For the % MGI data, a one-way analysis of variance was performed with prior transformation of the original data using the formula: y = arsin [sqrt (y/100)]. The treatment means were compared using Tukey’s multiple range test (p = 0.05). Variance analyses were performed using SAS ver. 9.4 for Windows (SAS Institute, Cary, NC, USA). IC50 and IC95 values with 95% confidence intervals were calculated for EEs and effective fractions using a probit analysis.
4
Mycelial Growth Inhibition Assay
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The experimental design was completely randomized. The percentage data for the inhibition of mycelial growth, sporulation, and conidial germination by not complying with the assumptions of normality of these data were arcsine square-root-transformed before calculating an ANOVA. Tukey’s test (p ≤ 0.05) was used, and separation of means was carried out with the SAS ver. 9.4. for Windows (SAS Institute, Cary, NC, USA) for all analyses.
5
Probit Analysis of Antifungal Activity
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A one-way analysis of variance was performed with the prior transformation of the original % MGI and severity fruits data using the formula y = arsin [sqrt (y/100)]. The treatment means were compared using Tukey’s multiple range test (p = 0.05). Variance analyses were performed using SAS ver. 9.4 for Windows (SAS Institute, Cary, NC, USA). Using probit analysis, the IC50 and IC95 values for the extracts and effective fractions were calculated (95% confidence intervals).
6
Prognostic Factors in Prostate Cancer
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Different distributions of all independent prognostic variables recorded were compared according to presence or absence of BCR, CR and PcD using Wilcoxon non-parametric test for dichotomic and Mann Whitney U-test for continuous variables.
For univariate analysis Kaplan-Meyer curves were plotted for each independent variable (age, PSA, GS, positive and percentage of positive nodes, surgical margins status, height, weight, BMI, Charlson Score, Ki-67, topoisomerase II and miR-221) according to BCR, CR and PcD respectively. Cox proportional-hazards regression models to predict Biochemical and clinical recurrence (CR) as multivariate analysis. Statistics were conducted using SAS ver. 9.4 for Windows (SAS Institute, Cary, NC, USA) software package. P values of ≤0.05 were considered significant.
For univariate analysis Kaplan-Meyer curves were plotted for each independent variable (age, PSA, GS, positive and percentage of positive nodes, surgical margins status, height, weight, BMI, Charlson Score, Ki-67, topoisomerase II and miR-221) according to BCR, CR and PcD respectively. Cox proportional-hazards regression models to predict Biochemical and clinical recurrence (CR) as multivariate analysis. Statistics were conducted using SAS ver. 9.4 for Windows (SAS Institute, Cary, NC, USA) software package. P values of ≤0.05 were considered significant.
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