Sas version 9.4 statistical package

Data collected for carcass composition and meat quality were analyzed using the general linear model (GLM) procedure of the SAS Version 9.4 statistical package (SAS Institute Inc. Cary, NC, USA, 2016). The linear model used for carcass composition traits (carcass characteristics, internal organs and non-carcass components) was $Y_{ij}=\mathit{\mu }+S_i+e_{ij}$ , where $Y_{ij}$ is the response variable, $\mathit{\mu }$ is the overall mean common to all observations, $S_i$ is the effect of $i$ th sex (male and female), $e_{ij}$ is the random error with a mean of 0, and variance is ${\mathit{\sigma }}^{\mathrm{2}}$ , whereas meat quality traits (physicochemical and sensory attributes) were analyzed using the following linear model: $Y_{ijk}=\mathit{\mu }+S_i+M_j+$  ( $S$   $\times$   $M$ ) ${}_{ij}+e_{ijk}$ , where $Y_{ijk}$ is the response variable, $\mathit{\mu }$ is the overall mean common to all observations, $S_i$ is the effect of $i$ th sex (male and female), $M_j$ is the effect of $j$ th muscle type (breast and leg), ( $S$   $\times$   $M$ ) ${}_{ij}$ is the sex by muscle type interaction, $e_{ijk}$ is the random error with a mean of 0, and variance is ${\mathit{\sigma }}^{\mathrm{2}}$ . Normal distribution of the variables was analyzed according to the Shapiro–Wilk test. The results are presented as least-square means  $\pm$  standard error of the mean (SEM). None of the interactions were significant and are therefore not reported in the results. Differences were considered significant at the level of $P\le \mathrm{0.05}$ . For statistical analyses, each bird was considered the experimental unit.

Log-binomial models for longitudinal data were run to evaluate the association between patient’s characteristics and the probability of success of smoking cessation overall and at the different times of evaluation (i.e. 3, 6, and 12 months). To account for correlation within subjects, the generalized estimating equations (GEE) method was used. A firstorder autoregressive working correlation structure was specified in the model. We derived relative risks (RRs) and corresponding 95% confidence intervals (CIs) after adjustment for sex, age, FTND score, and self-efficacy. Self-efficacy, age, and FTND score were considered in approximate tertiles.
Statistical analyses were conducted with the SAS version 9.4 statistical package (SAS Institute, Cary, NC, USA). The statistical significance level was set at a two-tailed p<0.05.