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Then, we propose a new method to minimize the energy by optimizing all the variables of the model.
Finally, the third model (Model C) includes all the variables of Model A and all the variables describing the substitution groups.
Since the model monitors human populations, all the variables and parameters of the model are nonnegative.
Next we show all variables of the babesiosis model living in Ω for all time (tgeq0).
This model uses the variables of model I plus all simple squares of the primary data.
All independent variables in the models are school-level variables, and the resulting measures of association are prevalence ratios (PRs).
All categorical variables entered the models as indicator variables.
As none of the variables were highly correlated, all the variables were included in the logistic model.
Multivariate (adjusted) models were used to identify variables predictive of malnutrition, controlling for all other variables in the model.
None of the variables were highly correlated (r >0.6), so all the variables were included in the logistic model.
To ensure independence of all variables in the model, we intentionally included only these three confounding variables that we considered to be fully independent of the presence of a protected area.
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