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Alternatively, consistent point estimates with somewhat larger standard errors can be obtained by bootstrapping the three-steps procedure described above.
Confidence intervals for the migration response could potentially be obtained by bootstrapping methods, but this has not been done either by Blanchard and Katz (1992) or by recent contributions like Beyer and Smets (2015).
Its standard error can be obtained by bootstrapping.
If none of these methods seem to give an adequate description of the data, the intervention and control group will be compared using the van Elteren test, and a non-parametric estimate of the confidence interval of the intervention effect will be obtained by bootstrapping [ 16, 17].
Evaluation of the estimated threshold can be performed by a significance test for the existence of a threshold using a modified likelihood ratio test which follows a chi-squared distribution with 3 degrees of freedom, and confidence intervals for the threshold can be obtained by bootstrapping.
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All standard errors are obtained by bootstrapping with 1000 replications.
The confidence intervals were obtained by bootstrapping as before.
Standard errors for kernel and local linear matching and inverse probability weighting are obtained by bootstrapping with 1000 replications.
For all analyses, trees confidence values were obtained by bootstrapping 100 data sets (SEQBOOT).
Correspondingly, the same significant pattern was obtained by bootstrapping the average number of substitutions per site (Dxy, not shown).
Statistical support for internal branches of each tree was obtained by bootstrapping (1000 replicates for the NJ trees; 200 replicates for the ML trees).
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