Sas package 9

Statistical analyses were performed using the analysis of variance for continuous data and the chi-square exact test for categorical variables. Bonferroni correction was used for multiple comparison analyses. The generalized linear model analysis (gamma with log link) was used to make comparisons between surgical procedures and operative results. Generalized estimating equation (GEE) analysis was used to make comparisons between surgical procedures and longitudinal data on eGFR. The risk ratio was used to make comparisons between surgical procedures and incidence of complication rates. The analyses were performed using donor sex and laparoscopic donor nephrectomy as adjustment factors. P values of <0.05 were considered statistically significant. Analyses were performed using SAS package 9.0 (SAS Institute, Cary, NC).

This experiment was conducted as a completely randomized block design (moisture levels and presence of ThzID1-M3 pellet treated as factors, and sampling times as blocks). All analyses were performed using SAS package 9.0 (SAS Institute Inc., USA). Recoverable numbers of bacteria, Trichoderma spp., and ThzID1-M3 were standardized by gravimetric soil moisture and log-transformed prior to analysis. Analysis of variance using PROC GLM was performed for analyzing microbial populations and ThzID1-M3 biomass in soil, and for ThzID1-M3 DNA estimates in sclerotia, with significant differences at p < 0.05.

Descriptive statistics for milk composition traits (FP, CPP, MU) and ECPU were performed for 634 cows using the MEANS procedure of SAS package 9.4 (SAS Institute Inc. 2013, Cary, NC, USA).

The data collected were subjected to four-way ANOVA (Analysis of Variance): pot (accessions, strains, soil status, and season), field (accessions, strains, locations, and seasons) statistical analysis system (SAS) package 9.4, and means were separated using the Duncan Multiple Range Test (Dmrt) at p ≤ 0.05 (Zatybekov et al., 2017 (link)).

The data from the in vitro and in vivo experiments were analyzed using the general linear model procedure of the SAS package 9.4 (SAS Institute Inc., Carey, NC, USA). The general linear model for the statistical analysis is as follows:
where y_ij is the jth observation in the ith treatment, μ is the overall mean, τ_i is the fixed effect of the ith treatment, and e_ij is the unexplained random effect on the jth observation for the ith treatment. Differences between treatments were analyzed using the Tukey test, with statistical significance declared at p<0.05 and a trend discussed at 0.05≤p<0.1.

The data were statistically analyzed using analysis of variance (ANOVA) for a completely randomized block design with SAS package 9.4 software and the differences in means were determined by the least significant differences (LSD). Duncan’s multiple-range test was performed at P ≤ 0.05 on each of the significant variables measured. P values less than 0.05 were considered as statistically significant.