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Data were analyzed as a randomized complete block design using the GLM procedure.
The statistical analysis was performed using the GLM procedure of SAS (2003) in one-way ANOVA design.
The statistical model in Equation 1 was fitted using the GLM procedure in SAS software (SAS Institute Inc. 2004 2009).
Data were analyzed using the GLM procedure of SAS for a completely randomized design and significance level was set at 0.05.
Statistical analysis was performed using the GLM procedure of SAS (1992) for a completely randomized design with a 2 × 2 factorial arrangement.
Steers were fed for 27 days in year 1 and 28 days in year 2. Performance data were analyzed across years using the GLM procedure of SAS and health data were analyzed across years using χ2.
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All data were subjected to analysis of variance using the GLM procedures of the statistical analysis system (SAS Institute, U.S).
All data were analyzed using the GLM procedures of SAS software (SAS Institute, Inc., Cary, NC, USA), with each replicate pen as the experiment unit.
We analyzed survival data in a generalized linear mixed-model framework using the glmer procedure (and glm when we included only fixed effects) in the lme4a package of R, and development time data in a linear mixed-model framework using the lmer procedure in the lme4 package of R R Development Core Teamm 2008).
The MIXED procedure, a generalization of the standard linear model used in the GLM procedure, was used to examine independent relationships of longitudinal changes in BMI, SI, and AIR with changes in SG, BIE, and GEZI.
The means and covariances are shown in Table 2. Again, the analysis was carried out using the GLM (repeated measures) procedure in SPSS and within a SEM package (Mx).
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