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Histology data were analysed with a general linear model, univariate analysis and Tukey post hoc test.
General linear model univariate analysis was employed to compare data between attitudinal score and each independent norminal demographic variable.
Chi square, fisher exact test, and general linear model univariate analysis were used to compare data between independent cohorts.
Interaction between gene polymorphisms in modulating BMI and fat mass was tested by, age weighted, general linear model univariate analysis.
In the first model, univariate analysis of all variables (age, season, and year) except clinical signs yielded p<0.25.
Two-way ANOVA (General Linearised Model, univariate analysis, with genotype and diet as fixed factors in SPSS17) was used to assess embryo weight and organ measurements.
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Prior to the construction of the models, univariate analysis of variance was conducted to verify whether or not there was an interaction effect between the consumption of medicines and age influencing patients' knowledge.
Model I: Univariate analysis, Model II: Multivariate analysis; aOdd ratios; bConfidence intervals.
Multivariate analysis was carried out using a forward stepwise hazard model on univariate analysis required for entry into the model.
In combined analysis, we used General linear model (GLM) univariate analysis with continuous phenotypes as dependent variable, semi-continuous SNP genotype as independent variable under an additive model and study stage, sex, age and BMI as covariates for adjustment.
In the dominant genetic model, univariate survival analysis indicated that MIBC patients with allele G (TG/GG genotype) had a significantly decreased risk for death than patients without allele G (TT genotype) (HR = 0.21, 95 % CI = 0.05 0.90, P = 0.035) (Fig. 2).
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