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The expected population effect is derived using a simple mathematical model in the additional material [Additional file 1].
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Expected population effects from improved public health practices are investigated in the section 'Results and discussion' through numerical simulations of the model using a set of plausible parameter values abound in literature.
In the case of a stochastic quantal endpoint, M H is the "individual probability of effect," which, averaged over the population in Equation 15, would be, by definition, equal to the expected population incidence of effect.
For a stochastic quantal endpoint, this equals the expected population incidence of the quantal effect.
Then one would expect population size effects on the rate of molecular evolution.
MANTRA expects populations with similar genetic ancestries to have more closely matched effect sizes, while allowing for greater heterogeneity in the effects observed for more diverse populations.
This is why researchers expected that massively treating HIV-infected people in a community would have a discernible "population effect" on that group.
To assess the purity of the isolated cells, we confirmed that Cd11b mRNA was expressed only in CD11b+ cells, as expected [main effect of cell population, F 1,64) = 71.68, p < 0.001] (see Supplemental Material, Figure S2A).
The control variables i.e. demographic structure (share of female, elderly population and urban population) and health condition (life expectancy at birth) showed expected effect on any kind of health expenditures.
As would be expected, the effect becomes stronger if the estimation is reduced to the target population in columns (3)–(6).
Assuming that the same causative mutations, or even the same gene regions but different causative mutations, act on traits of interest in different populations, it is expected that effects of chromosome regions on a trait could be consistent among populations, though the LD patterns between individual SNPs and QTLs could differ from one population to the other.
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