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Genotypes found to be (borderline) significant in the univariate logistic regression models were carried forward to the multivariate model, adjusting for covariates with P < 0.1.
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The best performing structural model was carried forward to covariate model building, where all available oral and intravenous data were used.
The final model was carried forward for GLMM analysis incorporating a random variable called 'farm cluster' which records the temporal/spatial nature of the sampling carried out during the IPRAVE survey.
The data were fit using a robust linear regression model (rlm function from R statistical package), and the residuals with respect to the model fit were carried forward in all subsequence analyses as the gene expression traits.
The data were fit using a robust linear regression model (rim function from R statistical package), and then the residuals with respect to the model fit were carried forward in all subsequent analysis.
Extracted data were pooled by means of both random and fixed effects models, and subgroup analyses were carried forward to compare findings in ICU versus non-ICU patients.
Significant covariates were carried forward into more completely adjusted models, and model simplifications including treating SES and age at diagnosis as an ordered categorical variable were also considered.
Covariates with P-values < 0.2 in bivariable analyses were carried forward to the multivariable model.
All factors were analysed for a univariate association with BSI and any variables meeting the Greenland entry criteria (p<0.2) were carried forward into a final multivariable model.
These were carried forward from the prior study day.
Axioms 1-10 were carried forward from [ 12].
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