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The simulations suggest that amalgamation of posterior probabilities from the tree gives approximately unbiased estimates, and standard errors can be calculated using a cluster bootstrap approach with cluster effects included in the predictions.
We estimated 95% CIs of proportions by using a cluster bootstrap technique with 1000 resamples [13].
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We used a cluster bootstrap procedure in which clusters are selected by simple random sampling with replacement and there is no subsequent permutation [ 34].
We used a cluster bootstrapping technique for the calculation of 95% confidence intervals (95% CI) [ 18]. 2. We used the generalized estimating equations (GEE) approach to fit logistic regression models [ 19] for evaluation and comparison of SAR between intervention groups.
Congruence between morphological and molecular species limits was 97.8% when using a clustering approach with high bootstrap support and enforcing a monophyly requirement in the molecular results, while clustering and identification success was 99% using clustering with a relaxed bootstrap criterion.
The relationship between physician-assessed FN risk and model-predicted risk was estimated using penalized splines with a cluster bootstrap to produce pointwise confidence limits 17.
A cluster bootstrap was used for sampling PML and non-PML patients with replacement.
Here we used a cluster robust variance estimator and a cluster bootstrap to estimate the standard errors of the coefficients (in addition to a robust standard error estimator that ignores clustering).
We determine the statistical significance of association between the mth miRNA cluster and nth mRNA cluster using a non-parametric bootstrap test.
We then inferred the best clustering from our qRT-PCR gene expression data by using a multiscale bootstrap resampling: this partitioning method ensures the representation of the most significant differences between genes belonging to different clusters.
This paper estimates Eq. (2) using a block bootstrap method.
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