Data from: On the variety of methods for calculating confidence intervals by bootstrapping

1. Researchers often want to place a confidence interval around estimated
parameter values calculated from a sample. This is commonly implemented by
bootstrapping. There are several different frequently used bootstrapping
methods for this purpose. 2. Here we demonstrate that authors of recent
papers frequently do not specify the method they have used and that
different methods can produce markedly different confidence intervals for
the same sample and parameter estimate. 3. We encourage authors to be more
explicit about the method they use (and number of bootstrap resamples
used). 4. We recommend the bias corrected and accelerated method as giving
generally good performance; although researchers should be warned that
coverage of bootstrap confidence intervals is characteristically less than
the specified nominal level, and confidence interval evaluation by any
method can be unreliable for small samples in some situations.