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CD4 cell count at viral set-point was modelled using linear regression models.
The dynamics of the variables was modelled using linear mixed-effect models with a random intercept and slope and compared [23].
Independent predictors were modelled using linear and logistic regression analyses.
Associations between dependent and independent variables were modelled using linear regression.
The relationship between component scores and psychosocial scales was modelled using linear regression.
The indices for antenatal care and newborn care practices followed largely normal distributions and were modelled using linear regression.
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The shell is modelled by using linear shell theory; classical lamination theory is used to determine the stiffness of the overall composite shell structure.
This approach allows sets of relationships between variables to be modelled simultaneously, using linear or logistic regression as appropriate according to the form of the dependent variables and with the mediating variables being treated as both dependent and independent variables.
Costs and QALYs were modelled using generalized linear models whilst MACE was modelled using logistic regression.
The index for delivery care practices, however, followed a Poisson distribution and was therefore modelled using generalized linear modelling.
Standard Models: All of the combinations of age groups and time periods, described above, were modelled using both linear regression (300 models) and Poisson regression (675 models).
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