Sas statistical software package version 7

The data analyses were performed using the SAS statistical software package version 7.1 (SAS Inst., Cary, NC, USA). Mean values, as well as the standard deviation (SD), were calculated for all parameters. The study was based on a two-factorial (farrowing system vs. BW) trial. By means of the Shapiro-Wilks test and Kolmogorow-Smirnov test, the parameters were checked for normal distribution. In the case of normally distributed data, the Ryan-Einot-Gabriel-Welsch multiple range test (REGWQ) was used for reproductive parameters (parity, number of total born/ live-born/stillborn piglets, number of piglets after litter equalisation, weaned piglets, piglet losses), IC and daily weight gain to detect significant differences between housing systems. For the availability of normally distributed data, the two-sample t-test was used to compare IC and daily weight gain between light and heavy piglets. To compare the concentrations of the AAs between housing systems and weight classes (light vs. heavy), a nonparametric test (Kruskal-Wallis-test) was used because of their non-normal distribution. This was followed by a pairwise comparison with the Wilcoxon two-sample test. Statistical significance was considered when p < 0.05.

The data analyses were performed using the SAS statistical software package version 7.1 (SAS Inst., Cary, NC, USA). Mean values, as well as the standard deviation of the mean (SD), were calculated for all parameters, as well as individual BW and carcass weights. The mean FPD-scores were evaluated by using the mean of both feet. The feed and water intakes, FCR, W:F-ratio, and percent DM content in litter were estimated at the pen level, as well as the final BW and FPD for correlation analysis. For the description of the prevalence of FPD, two-dimensional frequency distributions of categorical features were checked for dependency by means of the Pearson‘s chi square homogeneity test.
The group comparisons were performed by one-way analysis of variance (ANOVA) for independent samples. The Ryan-Einot-Gabriel-Welsch multiple range test (REGWQ) was used for multiple pairwise means comparisons between the four groups of flooring design. A Pearson’s correlation coefficient was calculated to evaluate the relationship between the final BW and final FPD-scores at the pen level between groups. All statements of statistical significance were based on p < 0.05.

Data analysis was performed using the SAS statistical software package, version 7.1 (SAS Inst., Cary, NC, United States). After classification of Campylobacter contamination levels of chicken carcass neck samples and human cases, both characteristics were shown and descriptively analysed using table analyses. Pearson’s chi-square homogeneity test was used to determine if there was an association between the two parameters. Cohen’s kappa coefficient as a descriptive measure of agreement was analysed and evaluated according to Altman: values of <0.20 are poor, 0.21–0.40 fair, 0.41–0.60 moderate, 0.61–0.80 good and 0.81–1.00 very good (29 ). In addition, the McNemar test was used for differences in the marginal distributions.
The data on private consumption behavior of fresh chicken meat were analysed descriptively by mean values, minimum, maximum and standard deviation. To test for normal distribution, a Shapiro–Wilk test was performed. Data were checked for significant differences with the Ryan-Einot-Gabriel-Welsch-test (one-way ANOVA). All statements of statistical significance were based on p < 0.05.