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A non-parametric approach, for example using a null bootstrap estimator, might be more accurate.
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We used a null model incorporating a bootstrap randomization procedure to examine whether ovarian cycles were more synchronous or asynchronous than expected by chance in a large captive hamadryas colony.
We estimated this null distribution using a permutation bootstrap, in which we randomly swapped the assignments of ai and bi and recomputed AUC a)–AUC(b).
POTION first tries to calculate q-values using the qvalue method as described in [ 25] and implemented in Statistics:Multtest Perl module, estimating the proportion of true null hypotheses using a bootstrap procedure.
We validated each model using a bootstrap method (10,000-iteration) and reported the bootstrap bias-corrected AUCs with 95% bootstrap confidence interval (CI) (15).
This paper estimates Eq. (2) using a block bootstrap method.
To estimate the number of false positives, we generated a distribution of null test statistics corresponding to an interaction term, while preserving the main effects of the SNP and exposure terms, using a parametric bootstrap method (Bůžková et al. 2011).
For comparison of single unit parameters, we checked whether the difference in values between two time-points for a given unit significantly deviated from a null (zero centered) distribution using a bootstrapping method (see 'bootstrap.m' in Source code 1).
Field-significance was tested using a bootstrap approach.
Confidence intervals (CI) were calculated using a 1000 repetitions bootstrap.
The Probability Density Function (PDF) of those coefficients was calculated using a bootstrap technique.
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