Coefficients reported for the Poisson part indicate the influence of a given covariate on the expected count of dual VET years accumulated for people belonging to the possibly positive outcome group.
In the latter case, a change of sign simply indicates that a variable has, for instance, a positive effect on the probability to belong to the always zero group, i.e., those getting no years of dual VET, and a negative effect on the expected count for the other group of students, those who may get a positive count.
The expected count is based on the reporting frequency of product inadequacy only within reports on the same product, to control for the variation between different products' therapeutic success rates.
The whole-body scanning speeds varied between 10 and 20 cm min−1 depending on the expected count rates from the subject on each day of imaging leading to total whole-body scanning times of between 10 and 20 min.
This fine grained analysis is made possible by the two part structure of our model, as either a simple Poisson or a negative Binomial model both estimate a negative impact of the grade on the expected count, and a large positive impact of being in the low track, both results due to the comparatively large magnitude of the negative selection into dual VET.
The actual number of added cases was random and followed Poisson distribution centered on the expected count.
VA ESSENCE determines an expected count by employing regression modeling based on historical data, day-of-the week effects, seasonal trends and effects due to other factors[7].
VA ESSENCE determines an expected count by employing regression modeling based on historical data, day-of-the week effects, seasonal trends and effects due to other factors.
On the basis of the expected count, every individual may get multiple copies.
This was based on two cases observed versus a very small expected count.
