There were stepwise decreases across quintiles for both parameters, from 69% (HOMA S) and 35.7% (B × S) (Q I) to 39% (HOMA S) and 22.5% (B × S) (Q V) (both p < 0.0001).
The mean and standard deviation of the ratio from each study were calculated from the raw data, or estimated by probabilistic simulation, and showed a generally close agreement across studies for both parameters.
Analysis of the data for dose proportionality showed that the 95 % CI of selexipag and ACT-333679 for the slope included 1 for both Cmax and AUC0 ∞, suggesting an approximate dose-proportional increase in both parameters across the doses tested (data not shown).
This p-box represents both parameter variability across flows, and epistemic uncertainty within each calibration.
In addition to selecting markers with low Q values from the BL-Y1 dataset, we used the Y1 colonies from the two different apiaries and selected proteins that had P < .05 across all field parameters in both datasets.
Tests comparing the pooled and fully interacted models as well as comparing the joint effects of parameters across both outcome categories were conducted using adjusted Wald tests.
The measure also demonstrated equivalence of fit and parameters across both the male and female subsamples, therefore demonstrating validity of use of the measure across both males and females, and in mixed gender groups.
Moreover, the model that allowed all of the parameters of the Richards' growth function to have different values for the L and H pre-mating groups (Model 2, Table 4) was significantly better than the model that had the same parameters across both pre-mating groups (Model 1, Table 4).
When looking at each specific parameter, the models that allowed only μ or only λ to vary between the L and H pre-mating groups (Models 4 and 5, Table 4, Figure 3) were also significantly better than the model that had the same parameters across both pre-mating groups (Model 1, Table 4).
Moreover, allowing two parameters (only μ or only λ) of the Richard's growth function to vary between the low and high density pre-mating groups resulted in significantly better fit than a model that had the same parameters across both pre-mating groups (Table 4).
