Sas software for windows

A descriptive analysis was performed to assess all the obtained data. Continuous quantitative variables were described as medians and interquartile ranges, and categorical qualitative variables as frequencies and percentages (%). The continuous variables are graphically represented using boxplots [the box shows the first (Q1), second (median), and third quartiles (Q3), and as whiskers, the values correspond to 1.5 times Q3] and categorical variables using bar graphs. The quantitative variables were compared using the non‐parametric Mann–Whitney test and qualitative variables using the chi‐square test or Fisher's exact test. Stepwise multivariate logistic regression analysis was used to calculate the adjusted risks (odds), respective 95% confidence intervals, and probability (p‐value) of developing peri‐implantitis and mucositis. All analyses were performed using SAS for Windows Software (Version 9.4, SAS Institute). All statistical tests were applied to 2 sails, and values were considered significant if the calculated probability was <0.05. The following two types of analyses were performed: the first analyzed the variables individually in the entire study population and the other in the population divided into two groups according to the type of implant‐prosthetic rehabilitation performed.

The food consumptions were energy adjusted using the residual method (Willett 2012 ), which is an established and a widely used method in nutritional epidemiology to enable the investigation of the quality, rather than the quantity, of foods in the diet. Energy-adjusted intake variables were computed as the residuals from the regression model, with total energy intake as the independent and the food consumption as the dependent variable. Multivariate analysis of variance (ANOVA) models were used to investigate the group differences in food consumption between the AVI/AVI and PAV/PAV genotypes, and an additive linear regression analysis was carried out to examine the allele-specific effects of the hTAS2R38 genotypes. All models were adjusted for age, and the multivariate models were further adjusted for total energy and body mass index (BMI). The women and men were studied separately. All statistical analyses were performed with the SAS for Windows software package version 9.3 (SAS Institute Inc., Cary, NC).

The gene expression of TLR2, TLR4, IL-12, IFN-γ, TNF-α, IL-10 and TGF-β was compared using ANOVA in repeated-measurement design on time, followed by an adjusted Tukey's test for multiple comparisons when the data presented a normal distribution. In the case of a non-normal distribution of data on TLR2, TLR4, IL-12, IFN-γ, TNF-α, IL-10, TGF-β and IL-17 levels in patients and controls, the same design was fitted using a generalized linear model with a gamma distribution. Differences in values for sputum smears between groups of patients were assessed using a Kruskal-Wallis test with Dunn's post-test All of the analyses were performed using SAS for Windows software, V.9.2. The results were considered significant when p<0.05.