Sas university edition

Results of antimicrobial efficiencies, including growth inhibition zone diameters and the lowest concentrations of MIC and MBC, of the acids among specific pathogens were described as means ± standard error of the mean (SEM). The antimicrobial efficiencies data were tested for their normal distribution for each pathogen. Logarithm transformation was applied for non-normally distributed data. Differences in growth inhibition zone, MIC and MBC among the four acids for each pathogen were calculated by applying the one-way analysis of variance (ANOVA), and Tukey’s multiple-range tests, SAS^® University Edition, were used for pairwise comparison. Significance was defined as p < 0.05.

Statistical analysis was carried out using SAS University Edition (SAS Institute, Inc, Cary, NC). Descriptive statistics are presented as mean ± SEM. One-way ANOVA was used to compare differences in tumor variables between groups. Differences in apoptosis, proliferation, gene expression, citrate synthase activity and, densitometric values were evaluated using t-tests. For all tests, p < 0.05 was considered statistically significant.

Existing univariate and multivariable analysis methods for examining associations are not directly transferable to RDS samples because random sampling assumptions are not satisfied. Bivariate associations between exposure to discrimination by a healthcare provider and the outcome of an unmet health need were explored using unadjusted odds ratios. Following this, stratified odds ratios were calculated for each social determinant of health, including access to a regular healthcare provider and socio-demographic factors (gender, age, education level, employment status, food security, mobility in the past 12 months, and income level).
RDS weights were calculated, using the RDS-II weighting estimator developed by Volz and Heckathorn, along with wave number, for each eligible participant through the RDS Analyst program, powered by the statistical package R (Volz and Heckathorn 2008 ; Handcock et al. 2014 ). Prevalence estimates and unstratified and stratified odds ratios for the associations of interest were calculated with 95% confidence intervals in SAS® University Edition (SAS Institute Inc. SAS® University Edition for OS X 2016 ).

All data were analyzed with PROC MIXED including in the model the effects of diet and feeding duration as fixed effects for repeated measures using SAS University Edition (SAS Institute Inc., Cary, NC). For measurement comparisons, we used the least mean square algorithm and performed Tukey–Kramer multiple-comparison adjustment. We also used linear regression to analyze the correlation between UCrn and UUN in each diet in Experiment 1. Regression line slopes were compared with the analysis of covariance. For all analyses, the level of statistical significance was set at 5% (P < 0.05). Values were presented as mean ± standard error.

All quantitative data were expressed as mean ± SEM. Western blot data were analyzed using unpaired t-test in GraphPad Prism6 (GraphPad Software, CA, USA). Behavioral data were analyzed using unpaired t-test, paired t-test, or two-way repeated measures ANOVAs in SAS University Edition (SAS institute, NC, USA). P-values < 0.05 were considered to denote significance.

For each bull, averages of the data from the left and right testicles for linear measurements, as well as for histopathology, were used. The data of testicular biometry, sperm analysis, and testosterone concentration were initially tested for normality using the Shapiro-Wilk test. Analyses considered the main effects of treatment (CG, G1, and G2), time (days), and their interactions. The SAS GLIMMIX procedure with a REPEATED statement was used to account for auto-correlation between sequential measures (SAS University Edition, SAS Institute Inc., Cary, NC, USA). The model was adjusted for the type of distribution of each endpoint. Differences between means were compared using the Tukey test. Data of weight and carcass traits was analyzed using the GLIMMIX procedure of the SAS. The grades of seminiferous tubule degeneration were compared among groups using the Kruskal-Wallis non-parametric test. Associations between the degree of degeneration of the seminiferous tubules and other testicle parameters at day 90 were calculated using the Pearson’s correlation method. Results are presented as mean ± S.E.M. A P value lower than 0.05 indicated statistical significance.