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A multivariable regression was created using the same variables as above (see Table 4).
Multivariable regression was used in a cross-sectional analysis.
A modified grid search algorithm, incorporating multivariable regression, was used for parameter optimisation.
Multivariable regression was used to adjust for confounders including estimated leukocyte cell proportions and population substructure.
Multivariable regression was used to identify factors associated with GTT parameters.
Due to small numbers, a multivariable regression was not performed on the data (table 3).
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Stepwise multivariable regression is used to present equations for modelling shear link behavior parameters.
Results for multivariable regression are shown in Table 2.
Descriptive analysis and multivariable regression were performed using SAS (Version 9.1.3, SAS Institute Inc., NC 27513-2414, USA).
Age standardisation and multivariable regression were used to account for sociodemographic differences between the surveys.
Other variables associated with increased mortality on multivariable regression were insertion of external ventricular drain, age and decreased GCS.
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