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The mediating effect of affect was analyzed by using the bootstrapping method (see Table 4).
We show both the correlations calculated from the original datasets and the mean of correlations calculated using the bootstrapping method.
In the prediction scoring model, the c-statistic from internal validation using the bootstrapping method (number of repetitions = 1000) was comparable at 0.862 955% CI 0.795 0.930).
These significant results fulfill the prerequisite requirements for the mediation test using the bootstrapping method with bias-corrected confidence estimates [52].
The weekly averages of both citizen and expert observations and the 95% confidence intervals calculated using the bootstrapping method are presented in Figures 2, 3 and 4 for the years 2011, 2012 and 2013, respectively.
Citizen observations were compared with the visual observations performed by trained expert observers, and mean correlations between citizen and expert observations were calculated using the bootstrapping method: 0.72, 95% confidence interval (CI) [0.53 0.86]; 0.65, 95% CI [0.35 0.86]; and 0.56, 95% CI [0.29 0.76] for the years 2011, 2012 and 2013.
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The error bars are calculated using the bootstrap method with randomly selecting between 26 to 38 trajectories repeated for 100 times.
Error bars are calculated using the bootstrap method by using 10 subsamples each generated by randomly choosing 50 trajectories with replacement method yielding between 28 to 36 unique trajectories for each subsample.
Second, the effects of different cluster sampling designs on the precision of mean lengths were estimated using the bootstrap method.
Furthermore, we evaluate the large-sample formula for ICC estimates and standard errors using the bootstrap method.
Error bars for the free energy values are calculated using the bootstrap method on blocks of frames with 180 ± 70 ns time range that are randomly selected from all the trajectories in which Na+/Na2 is released to the intracellular environment.
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