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The calibration (Hosmer Lemeshow statistic) and discrimination (area under the curve, AUC) were calculated, and the model internally validated using a bootstrap methodology [17].
We calculated the nonparametric 2.5th and 97.5th percentiles, with their 90% confidence intervals (CIs), using a bootstrap methodology.
The ROC curves were also created by using a bootstrap methodology, which creates multiple samples (1,000) by randomly drawing instances, with replacement, from the original study population [ 36].
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Field-significance was tested using a bootstrap approach.
The Probability Density Function (PDF) of those coefficients was calculated using a bootstrap technique.
Optimal smoothing penalties are selected using cross-validation, and model uncertainty is quantified using a bootstrap re-sampling procedure.
We calculated power using a bootstrap approach.
CIs of RII and SII were estimated using a bootstrap procedure.
Each tree is built using a bootstrap sample of objects.
Standard errors were calculated using a bootstrap approach (10,000 resamples).
We calculated uncertainty estimates using a bootstrap procedure.
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