The OLS result in each of these two specifications shows that increases in the density of Hispanic immigrants in an occupation correspond to a decrease in wages of African-Americans, hovering around 3%%.
For each of these alternative specifications we found that the associated parameter ρ1 was statistically significantly different from zero.
The key parameter in each of these mathematical specifications is the transition rate: from S to I, from I to R and from R to I. If such modelling is to be helpful in infectious disease control, it is critical to have the best possible estimates of these rates (β, α and ν), as all three are important for modelling the spread of infection.
Finally, many of these specifications implement specifications that preclude facile extension of asserted knowledge.
See Table 1 for the listing of these specifications.
Because of this, most of these specifications can be arbitrary and, therefore, useless for comparison.
The chart that follows below is a bit technical, but consists of the t-statistic associated with the Iowa variable in a set of linear regression analyses using each of these six model specifications.
Each of these analyses entailed specification of a two-dimensional model (with one substantive trait, and one ERS trait) in which all items within the subscale tapped both dimensions, with each dimension having category slopes as specified for the model as in Equation 1.
The point estimate for the coefficient of the onsite MRI variable in each of these alternative regression model specifications is negative, which suggests the change in Medicare MRI volume for providers in MRI practices was lower than the change for non-MRI practices over the same time period, but all of the estimated coefficients are small in magnitude and not statistically significant (p > 0.05).
Qualitative networks, like Boolean networks, have a deterministic behavior, and it is therefore sufficient to perform one execution per initial state, and verify if each of these executions satisfies the specifications.
