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In multivariate regression modelling the parameter anemia showed the strongest significant relation to long-term outcome, along with established parameters such as age, hemorrhage volume, GCS, IVH, and presence of hemorrhage growth (Table 3A; OR: 3.0; CI (1.31-7.06); P < 0.01).
These comparisons show the potential power of modelling: the parameter values for the invariant part of the natural history of pre-clinical breast cancer are indeed the same, whereas the increase in the sensitivity reflects the improvement in mammography.
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In linear models, the parameter equals 1.0.
However, in this model, the parameter estimate is turned around.
In this model the parameter s denotes the period of the seasonality.
Thus, the final model included the parameter days in milk.
The uncertainties in the input parameters into the forward model cause the model parameter error.
However, these models clearly underestimate the parameter.
The utility values used in the model are shown in the model parameter Table 1.
Additional model description and the model parameter estimates can be found in our previous publication [ 23].
Various cost estimates used in the model are shown in the model parameter Table 1.
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