Velocities were calculated by using a bootstrapping procedure (mean±s.d.; N=1,000 bootstrap estimates from re-sampling with replacement).
(c) Velocities from a c without (black) and with (red) synaptic antagonists calculated by using a bootstrapping procedure (mean±s.d.; N=1000 bootstrap estimates from re-sampling with replacement; dots above the plot indicate significant differences, P-value <10−3, Mann–Whitney U-test).
The covariance structure software AMOS [ 30] was used to calculate the estimate path coefficients using a bootstrapping method (2000 bootstrap samples were used) [ 31].
The significance threshold was calculated empirically by permutation analysis (10,000 permutations), and the confidence interval for the QTL was defined using a bootstrapping approach (10,000 bootstrap samples).
CIs of the RERI were estimated by using a bootstrap method with 10,000 bootstrap samples in R statistical software, version 2.15.2 (http://www.r-project.org) [ 23].
In addition, we generated 95% confidence intervals for each value of PABAK using a bootstrap algorithm with 10,000 bootstrap samples [ 37].
Tree support was estimated using a bootstrap approach [ 60] with 100 bootstrap replicates, each followed by 100 random addition sequence replicates, followed by SPR branch-swapping.
Calculation of 95% confidence intervals (CIs) and coefficients of variation (CV) were determined using a bootstrap variance estimation method and bootstrap weights (provided by Statistics Canada).
95% CIs were estimated according to an adjusted bootstrap percentile CI by using a bootstrap CI of Light's kappa (Efron and Tibshirani 1993, Gwet 2010).
To perform an internal validation, we used a bootstrapping procedure (N = 500 bootstrap samples) to evaluate optimism of the parameters of models and calculated the odds ratio (OR) associated with inappropriate treatment and its 95% confidence interval (CI).
We did not use a bootstrap approach, because running bootstraps is often less intuitive for a policy and health plan audience and requires intensive computer resources.
