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The estimated coefficients (widehat {beta }_{20}, widehat {beta }_{21}) along with 90% bootstrap confidence intervals are shown in Table 2.

Bootstrap confidence intervals are listed.

Bootstrap confidence intervals are computationally demanding.

The estimates of the measures (with 95%% bootstrap confidence intervals) are displayed in Table 3.

Note that the 95% bootstrap confidence intervals are wider than those obtained from the delta method when considering conditional standardization.

We also note that the 95% bootstrap confidence intervals are slightly biased, with coverage probability somewhat <95% even with large N (Supplementary Fig. S6).

Here, a new approach to sensitivity index estimation using meta-models and bootstrap confidence intervals is described that provides solutions to these drawbacks.

All randomization p-values and bootstrap confidence intervals were based on at least 1,000 permutations/bootstraps.

To compare costs between groups, bootstrap confidence intervals were computed.

The sample size for the bootstrap confidence intervals was 999.

Bootstrap confidence intervals were calculated by 500 heuristic search replicates.