Sas software version 9

In-vitro bioactivity assays (Glucose uptake, hepatic glucose production and anti-inflammatory experiments) were subjected to a one-way analysis of variance (ANOVA) using SAS software version 9.1 (SAS institute Inc., Cary, NC, USA) with Dunnett’s post hoc test at a significant p value of 0.05 for acceptance. Peak areas of the chromatograms have been compared using a one-way analysis of variance (ANOVA) using SAS software version 9.1 (SAS institute Inc., Cary, NC, USA) with Tukey’s post hoc tests at a significant p value of 0.05 for acceptance.

Values of degree of conversion were statistically analyzed using t-Tests and post hoc Student–Newman–Keuls tests (SAS software, version 9.3; SAS Institute, Cary, NC, USA). Values of biaxial flexure strength were statistically analyzed using general linear models and Student–Newman–Keuls post hoc tests (SAS software, version 9.3; SAS Institute, Cary, NC, USA). Values of elastic modulus and roughness were statistically analyzed using one-way ANOVA and Tukey post hoc tests (JASP, v. 0.15, University of Amsterdam, The Netherlands). RLU values indicating the viability of non-disrupted biofilms of S. mutans grown against the surfaces of both unaltered and experimental dental adhesive resins were statistically analyzed using two-factor general linear models (GLM) and post hoc Student–Newman–Keuls tests (SAS software, version 9.3; SAS Institute, Cary, NC, USA). All tests were conducted with a level of significance of 95%.

The effect of amount of inoculum, particle size and incubation on ergosterol content, detergent fiber composition and IVGP was tested using the generalized linear model (GLM) analysis in SAS software version 9.3 (SAS Institute Inc., Cary, North Carolina, USA). The following model was used: ${\mathrm{Y}}_{\mathrm{i}\mathrm{j}\mathrm{k}}=\mathrm{\mu }+{\mathrm{\alpha }}_{\mathrm{i}}+{\mathrm{\beta }}_{\mathrm{j}}+{\mathrm{\gamma }}_{\mathrm{k}}+{\mathrm{\omega }}_{\mathrm{i}\mathrm{j}\mathrm{k}}$ in which Y_ijk is the observation at incubation time i; μ is the overall mean; α_i is the fixed effect of amount of inoculum i; β_j is the fixed effect of particle size j; γ_k is the fixed effect of incubation time k; ω_ijk is the random error.
The results of ergosterol measurements, chemical analysis and IVGP at different incubation times of the fungal treatment of each substrate, for each amount of inoculum and particle size combination, were compared using the generalized linear model (GLM) analysis in SAS software version 9.3 (SAS Institute Inc., Cary, North Carolina, USA). Post-hoc multiple comparison with Tukey’s significant test at a level of α = 0.05 was performed to determine the significance of differences between the treatments. The following model was used: ${\mathrm{Y}}_{\mathrm{i}\mathrm{j}}=\mathrm{\mu }+{\mathrm{\alpha }}_{\mathrm{i}}+{\mathrm{\omega }}_{\mathrm{i}\mathrm{j}}$ in which Y_ij is the observation j at incubation time i; μ is the overall mean; α_i is the fixed effect of incubation time i; ω_ij is the random error.

Counts of pots with symptoms after inoculation with the different Exserohilum and Bipolaris isolates were compared using a Chi² test in Microsoft Excel. Average disease intensity per plant (%) was calculated per block for the second trial. Analysis of variance (PROC GLM, SAS software version 9.2; SAS Institute Inc., Cary, NC) was used to determine significant differences in disease intensity (%) values among the Exserohilum and Bipolaris isolates, plant species and their interaction. Means for isolates and plant species were separated using Tukey's test. In the second experiment, areas under disease progress curve (AUDPC) values were calculated and compared with a generalized model analysis of variance using SAS statistical software (PROC GLM, SAS software version 9.2; SAS Institute Inc.). There were no effects of repetition or repetition–treatment interactions; therefore, the data of the repeated experiments were analyzed together. Furthermore, these data were log-transformed and regressed on time without intercept to quantify the relationship between log (% infection) and days after inoculation for individual combinations of C and P isolates of E. rostratum, rye grass, stilt grass, and blocks. Estimates for the slope were compared with a generalized model analysis of variance. Means were separated using Tukey's test.

Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to compare the proportions of HAT C. coli between C. coli sharing MLST STs with isolates from a human source and C. coli belonging to other MLST STs. OR and CI calculations were performed using SAS software version 9.4 (SAS Institute Inc., Cary, NC, USA). Mid-P exact tests were performed to assess differences in the levels of resistance to CIP according to aerotolerance levels of C. coli using SAS software version 9.4 (SAS Institute Inc., Cary, NC, USA).

Data were analyzed using general linear models with SAS software version 9.4 [38 ]. Rhipicephalus microplus, D. hominis larvae and H. irritans counts were not normally distributed and were log transformed (count + 1) to ensure normality, homogeneity of variances, residual analysis and randomness of the observations with back-transformed least squares means. The effects included in the model were ectoparasite counts, treatment and time point. A protected Student t-test was used for mean separation and the significance level set to 5% (P < 0.05).
Analysis of data for viable C. hominivorax larvae and egg mass (independent of the viability) in wounds was conducted using SAS software version 9.4 [38 ], and Fisher's non-parametric test was used for mean separation, with the significance level set to 5% (P < 0.05).