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This process creates what might be termed an ecology of predictors.
However, the optimal selection of predictors can be problematic when focusing on a localized region.
The proposed stepwise and lasso regressions reduce the number of predictors to a few.
However, insufficient patterns of predictors may reduce the model coverage and lead to poor generalization [44].
TN model gives stable variable importance rankings after assessing the relative importance of predictors.
A small sample of predictors is drawn at random (e.g., 3 predictors).
A new linear basis can be defined for each predictor and various sets of predictors.
This uncoupling of predictors of AKI and mortality was unexpected and may warrant further investigation.
We performed dominance analysis to compare the relative importance of predictors.
The first set of predictors consisted of the measured demographic variables.
A related problem stems from modeling strategies when a large number of predictors are present.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com