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Non parametric bootstrapping technique was applied to generate confidence intervals for cost data.
A bootstrapping technique was applied to the individual patient-level data of the pivotal cetuximab/irinotecan study (Cunningham et al, 2004).
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Additionally, when a bootstrapping resampling technique was applied on hierarchical clustering, the cells clustered based on their p53, RB, and INK4A status.
Bootstrap resampling technique was applied as an internal validation tool to assess the stability of the final parameter estimates and to confirm the robustness of the final model [ 20].
Finally, bootstrapping technique is also applied to the dual gate inverters that further boosts the noise margin and gain for DLL and ZVLL configurations.
This technique was applied to 1000 bootstrap samples.
Consecutive sampling technique was applied.
Manifest content analysis technique was applied.
Applying multiple testing corrections becomes problematic, as permutation or bootstrapping techniques are not feasible with small sample sizes.
Indeed, bootstrapping techniques are generally used in order to assess the accuracy of an estimator.
To estimate the mean ICER with a nonparametric 95% percentile confidence interval (CI), bootstrapping (10,000 resamples) techniques were applied to draw the cost-effectiveness plane and the ICER acceptability curve for the base-case scenario, in accordance with Spanish guidelines for economic evaluation of health technologies.
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