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Categorical covariates, for example, gender and genotype, were modelled using indicator variables.
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These were modelled using dichotomous indicators.
Predictor variables with more than two categories were modelled using sets of indicator variables.
Major social, economic and ecological functions for a sustainable spatial decision support in the suburban landscape are described and functionalised by indicators and modelled using GIS with the aim to minimise the problems related to the suburbanisation.
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.
CD4 cell count at viral set-point was modelled using linear regression models.
SASI is a recursive (i.e. equilibrium-seeking) model aimed at analysing the impacts of infrastructures and other major changes in the transport system on local economies, in which these impacts are modelled using regional production functions including spatially disaggregate accessibility indicators.
Any-stage AKI and stage-3 AKI were modelled using separate logistic regression models.
Rate variation among branches was modelled using the uncorrelated lognormal distribution (UCLD) model.
Gene-environment interactions were modelled using product terms again assuming an additive genetic model.
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