However, by modeling the proportion of TB treatment outcomes rather than patient counts with a large national sample, we aimed to minimize the effect of this selection bias.
By modeling the mean and proportion of expression as common across groups and adding specific random effects for between-individual variability, our model could be extended to address such experimental questions as well.
Among 2003 top 5% of actual users, 25.78% could be identified by the demographic model, 36.52% by model 2 and 41.67% by model 3; the proportion that could be identified by risk adjustment model alone was similar across three models, 10.5%.
As predicted by the DDC model, the proportion of paralogous genes in a state of subfunctionalization increases following the genome duplication (at t = 0), as degeneration of redundant inputs occurs.
For example, among 2003 top 1% of actual users, only 5.08% could be identified by the demographics model, 13.82% by model 2, 31.30% by model 3, and the proportion identified by risk adjustment models alone was much lower: 2.64%, 5.08%, and 6.10%, respectively.
At variance, by using the non linear model, the proportion of patients correctly predicted below or above the median value of actual EWL raised up to 70% 29%% + 41 % and 78% 45%% + 33%) for the 1st and the 4th quartiles, respectively.
We constrain the centres of the three genotype states on the basis of the expected A and R intensities for each state and approximate the weight of the Gaussian mixture model by the proportion of individuals in the population with a certain genotype.
Vaccination was modelled by reducing the proportion of susceptible individuals in the target population.
Site to site variation in substitution rate was modeled by estimating the proportion of invariant sites and assuming that rates among the remaining sites were gamma distributed (4 categories were used to discretize the gamma distribution).
It provides a measure of how well observed outcomes are replicated by the model, as the proportion of total variation of outcomes explained by the model.
