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MobiSim integrates several models representing demographic, social, economic, and spatial processes.
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We included categorical variables in the regression models, representing 5-year age groups and gender, to control for demographic confounders.
For this reason the simultaneous quantification of multiple biomarkers, that may include demographic/risk-factor(s), cervical length and biochemical marker(s), and the development of multivariate classification models represent a promising approach to improving diagnostic efficiency.
Demographic processes are not included because the model represents a single epidemic moving through a small population on a timescale of months.
The 2013 model represents year two.
This model represents an essential first step.
While most of these models focus on representing either forest demographics including age and height structure, or forest biogeochemistry including plant physiology and ecosystem carbon cycling, it is increasingly seen as crucial that forest ecosystem models include equally good representations of both.
In total, ten variables representing select demographic, clinical, or service use domains collected at baseline were examined in each regression model.
We are representing a demographic that is really real.
The movers represent multiple demographic trends.
ML models are represented by orange diamonds.
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