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To account for environmental stochasticity, the environment was modelled using independent and identically distributed sequences (Caswell 2001).
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Independent predictors were modelled using linear and logistic regression analyses.
Associations between dependent and independent variables were modelled using linear regression.
Education level was the independent variable and modelled using a categorical variable.
In this study, survival was directly modelled using classification models to optimise prediction accuracy.
Costs and QALYs were modelled using generalized linear models whilst MACE was modelled using logistic regression.
Mortality rates were modelled using Poisson regression model in which age and period midpoints were used as continuous independent variables, number of deaths as dependent variable, and logarithmic follow-up time in person years as offset.
CD4 cell count at viral set-point was modelled using linear regression models.
Environmental suitability was modelled using maximum entropy modelling (Maxent), a machine-learning process that uses presence-only data [6].
Any-stage AKI and stage-3 AKI were modelled using separate logistic regression models.
The main legs were modelled using beam elements, while the bracing members were modelled using truss elements.
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