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The significance of indirect paths will be tested via bootstrap sampling.
Caroline et al. [ 36] proposed a novel method to detect protein complexes by bootstrap sampling.
Bootstrap methods, using 500 sets of bootstrap sampling weights, were used to determine 95% CIs around each point estimate.
We applied the bootstrap sampling approach to our evaluation of the predictive validity of different ways of defining remission in RA.
Owing to our small sample size, a non-parametric CI for the estimate (mean) was constructed from the quartiles of the bootstrap sampling distribution of θ.
Test predictive model consistency using bootstrap sampling.
Error bars represent 68%% confidence intervals from bootstrap sampling.
The factor ranges are established by a preliminary study of bootstrap sampling.
The reader is directed to [14, 15] for more detailed explanations about bootstrap sampling.
To keep the study concise, bootstrap sampling was not studied here.
To solve it we used a bootstrap sampling module in the RapidMiner data mining software.
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