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The model variable that describes slow adaptation process was introduced for dynamical reasons and needs further physiological justification.
For model-based TGC, the patient-specific model variable that determines patient-specific state and response to therapy is the overall, whole body insulin sensitivity [42, 48, 73].
For model-based TGC, the patient-specific model variable that determines patient-specific state and response to therapy is the overall, whole body insulin sensitivity [ 42, 48, 73].
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These properties hold for the combination of representers that is associated with a group of observations and functions of model variables that combines model variables (e.g. salt flux).
A D-optimal design was used to identify and model variables that affect the transit time of wound exudate through an illustrative dressing used for negative pressure wound therapy.
One of the studies, conducted by James Murphy of the Hadley Center for Climate Prediction and Research in Exeter, U.K., and colleagues involved altering 29 climate model variables that control physical properties such as the behavior of clouds, atmospheric convection, and winds.
We kept in the final model variables that significantly enhanced the fit at the p<0.05 level.
We retained in the final model variables that enhanced the fit at the p<0.05 level.
In the final model, variables that were no longer associated with the outcome at p < 0.10 were allowed to drop.
In the multivariable model variables that were not significant and not confounding the effect of other variables in the model were removed.
To avoid overfitting, we manually removed from the model variables that were not associated with the outcome and used the Akaike Information Criterion to define the final model.
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