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Here, we apply standard bootstrap methods to correct for bias in the estimators and confidence intervals (see Efron and Tibshirani 1994; DiCiccio and Efron 1996) of some of the models studied above.
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For validation, we used a bootstrap-based method to correct for optimism in our estimates of incidence in each of the risk strata.
Therefore, we do not believe that bootstrap methods to produce verification bias corrected confidence intervals are appropriate.
We used bootstrap methods to compute 95% bias-corrected percentile confidence limits (CL) for restricted mean survival, survival gain from housing, and the cost per year of life saved [ 31]. Figure 1 displays the derivation and composition of the samples used in each of the analyses.
We use bootstrap methods to calculate cluster-robust standard errors (Efron 1979).
We adopted the bootstrap method to conduct regression analysis.
We used a bootstrap method to obtain confidence intervals [32].
We also used the bootstrap method to validate the reliability of the evolutionary tree branches with 1,000 bootstrap replications.
Loh (1987) also used a second layer of bootstrap resamples to correct confidence interval endpoints.
Correlations between character transitions were evaluated against 1000 bootstrap ML topologies to correct for phylogenetic bias.
*Result of bootstrapping technique used to correct for overoptimistic estimation of model.
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