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Optimal smoothing penalties are selected using cross-validation, and model uncertainty is quantified using a bootstrap re-sampling procedure.
Classifier gene selection was done by evaluating each gene using a bootstrap re-sampling method coupled with two-tailed t-statistics (described in the Methods).
Finally, the possible influence of sample bias and multicollinearity on the results was investigated using a bootstrap re-sampling procedure.
The confidence intervals were constructed using a bootstrap re-sampling technique and the information on total number of individuals tested per rayon.
The stability of the final model was investigated using a bootstrap re-sampling procedure as proposed by Sauerbrei and Schumacher (1992), applied in the context of HRQOL (Van Steen et al, 2002).
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Although the stability of sample and term configurations from CATA and RATA questions, calculated using a bootstrapping re-sampling approach, were similar, for two of the four studies RATA questions provided more stable sample and term configurations.
As we do not know the asymptotic distribution of such associations we used a bootstrap re-sampling scheme to construct the sampling distribution of the score β ij for testing the hypothesis.
Model calibration (similarity of predicted risks and proportions actually dying) was assessed graphically and used a bootstrap re-sampling to construct a bias-corrected calibration curve and its slope [25], [29].
Then, it uses a bootstrap re-sampling method to infer the optimized PWM scores.
A bootstrap re-sampling technique is used to estimate any sampling error in the survey when calculating the variances and confidence intervals [ 16].
A bootstrap re-sampling method was used to obtain confidence interval estimates for the MID and medium and large differences.
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