methods and compared their performance in terms of empirical coverage and width. We developed a bootstrap case cross …-validation (BCCV) resampling scheme and defined several confidence interval methods using BCCV with and without bias-correction. The … the literature tend to give overly conservative confidence intervals. Using BCCV resampling, the percentile confidence …

error rate. A general bootstrap algorithm is supplied to conveniently obtain consistent estimators of the null distribution … among the rejected hypotheses (van der Laan et al., 2004a). The proposed bootstrap multiple testing procedures are evaluated …

error rate. A general bootstrap algorithm is supplied to conveniently obtain consistent estimators of the null distribution … among the rejected hypotheses (van der Laan et al., 2004a). The proposed bootstrap multiple testing procedures are evaluated …

error rate. A general bootstrap algorithm is supplied to conveniently obtain consistent estimators of the null distribution. …

-statistics. Re-sampling based multiple testing (Westfall and Young, 1993) involves sampling from a joint null distribution of the … generally asymptotically valid null distribution for the test-statistics and a corresponding bootstrap estimate, whose marginal … illustrated that the resulting new re-sampling based multiple testing methods provide more accurate control of the wished Type …

resampling based methods, such as permutation methods, the null-centered and scaled bootstrap (NCSB) method, and the quantile-transformed-bootstrap … suffer from that limitation, but an impractical number of bootstrap samples are often needed to get proper control of Type I … paper compares the above three resampling based methods according to the control of family wise error rates (FWER) through …

maximization of log-likelihood with Cp, AIC, and BIC penalties, bootstrap and cross-validation error estimation, and coefficient …

It is a common practice to use resampling methods such as the bootstrap for calculating the p-value for each test when … performing large scale multiple testing. The precision of the bootstrap p-values and that of the false discovery rate (FDR … important need, we developed a simple adaptive bootstrap methodology for large scale multiple testing, which reduces the total …