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where S S i is a measure of severity of stroke at initial diagnosis (GCS or NIHSS), X i is a vector of other relevant risk factors (i.e., demographic and case-mix adjustments listed earlier) for the ith patient and the primary coefficient of interest is β1 which provides the odds ratio for admission to SU (by center c and outcome o).
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The primary coefficient of interest was β3, which captured the effect of the PBF program on the outcome Y.
The primary coefficient of interest is the triple interaction term (β7), which captures the difference in the impact of the program between the poor and the non-poor.
The primary coefficient of interest will be the time by group (control vs. intervention) interaction, which will indicate the degree of differential change across time between the control and intervention groups.
According to the above result, the weight-coefficient update and the primary user's signal detection are calculated in the meantime in the subsequent process.
The primary estimated coefficient of interest is β own_W, representing the difference in the dependent variable between private and public providers in Weifang, compared to β own for City Y, controlling for other observable characteristics.
Note that there are only N = tmax/h primary coefficient vectors, each corresponding to a Spline knot on the curve; the other coefficient values are deduced using some prescribed boundary conditions.
A detailed micromechanical analysis, using the mathematical theory of homogenization is conducted, to understand the coupled influence of damage mechanisms and volume fraction on the degradation of the primary stiffness coefficients.
The input model describing the ionospheric primary field is taken from CM4 (Sabaka et al., 2004) while the secondary, induced, field is calculated from those primary coefficients using the same 3D mantle conductivity model as for the magnetospheric induced field.
This paper proposes a new method of compromising adjustment solution based on target decomposition strategy and Error Correction Chaos Optimization (ECCO) algorithm to mainly acquire rational primary coefficients, and kinetics parameters when necessary.
Secondary, Earth-induced fields are determined (up to n = 15) from those primary coefficients using the 3D mantle conductivity model, including oceans, discussed in Kuvshinov et al. (2006).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com