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Using a nonparametric bootstrapping approach to mediation, the indirect effect is generated as a point estimate with 95% confidence intervals.
In the MP-EST analysis, 1000 bootstrap samples were produced using a nonparametric bootstrapping technique [ 47].
The reliability of the species tree inference was assessed using a nonparametric bootstrapping procedure resampling sites within individual genes [ 84].
The 95% confidence intervals relating to each percentage attenuation were estimated using a nonparametric bootstrapping method with 2000 re-samplings (with replacement).
We estimated a 95% confidence interval for the species survival by bootstrapping across populations using a nonparametric bootstrapping method in the boot package (Canty and Ripley 2014) in R (R Development Core Team, 2012).
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The model stability was validated using a nonparametric bootstrap (100 samples with replacement).
Confidence intervals for the model were obtained using a nonparametric bootstrap resampling procedure (n = 10,000 for each Monte Carlo data set).
For each attribute, the model with the lowest AICc value for the most data sets was selected as the best, and confidence intervals for the model parameters (and the utility threshold for nonlinear relationships) were obtained using a nonparametric bootstrap resampling procedure (n = 10,000 for each Monte Carlo data set).
ROC curve metrics were compared statistically using a nonparametric bootstrap method [ 63].
The final model was evaluated using a nonparametric bootstrap and visual predictive check.
We obtain standard errors for N − using a nonparametric bootstrap approach.
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