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Study size was planned using a bootstrapping strategy [ 23] on our previously analyzed retrospective data [ 15].
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The result is a matrix S where the final confidence score for is given by (18) To further improve inference and become more robust against over-fitting and sampling errors, we use a bootstrapping strategy.
They skipped data integration and used a bootstrap strategy instead, which consisted of iterative construction of Support Vector Machine (SVM) classifiers (on features selected for each iteration) based on randomly selected sets of specimen and testing the classifiers on the remaining samples.
These difference waveforms were compared using a bootstrapping procedure.
The mediation model was tested using a bootstrapping method.
The performance of all 80 strategies was determined for each of the three posture variables using a bootstrap procedure.
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.
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