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To assess the robustness of findings, we performed a sensitivity analysis by using restricted cubic splines for continuous predictors in the new model [37].
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Table 2 shows the predictors and their HRs included in the new model (Model 3) for 60-day hospital and 60-day ICU mortality.
Additionally, all the two-way interactions between the predictors in the new prediction model were tested.
The new model was pioneered in New York.
The new model is then applied to this external sample to obtain an independent estimate of the predictor's accuracy.
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Similarly, the performance of a model depends on the strength of the predictors in the model (ie, discrimination), as the model can be recalibrated to update it in time or to make it suitable for a new population.
Both the Hopelessness and Negative Affect items remained as independent predictors in the same model.
*Significant predictors in the full model.
A new set of predictors was generated which contained the predictors in the m-model, as well as all pair wise interactions between the predictors in the m-model.
This method tests a series of regression models, excluding in each new model the worst predictor of the previously tested model according to a statistical criterion (p ≥.10).
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