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Also, the predictive capacity of the model only works within the variation limits of the existing data, which means that the predictive value of the predictors that were not included in the model is questionable [ 11].
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Linear regression allows us to predict the outcome for a particular value of the predictor.
Accordingly, optimal prediction is formulated as the minimisation of the expected value of the predictor loss function [20,23,27,28,34].
Specifically, every side information pixel Y(p) is calculated as the mean value of the predictor values g k, u n : Y p = 1 N k, u n ∑ u n g k, u n, (4).
In categorical regression, the beta value is interpreted as the difference in the predicted value of the predictor variable for each one-unit difference in each response variable when others remain constant.
At a given time point, the value of the predictor variable was determined by the most recent prior measurement.
The difference is the average change in predicted probability resulting from having the population change from the first (reference) value of the predictor to the second (nonreference) value.
The algorithm requires knowledge of the most extreme value of the predictor variable on the day before or the day of admission for risk determination.
In other words, a negative hazard rate indicates increased survival chances with increasing value of the predictor variable (Therneau and Grambsch 2000).
A positive value indicates that increasing the value of the predictor resulted in decreased acceptability of the un- form, as would be predicted for the pre-emption and entrenchment measures.
c)The G önen & Heller's c-index is independent of the degree of censoring and is somewhat comparable to an area under the curve corresponding to a plot of the sensitivity versus positive predictive value of the predictor.
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