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More computationally intensive methods involving bootstrapping and permutation tests are becoming more common proposals in meta-analysis however and we anticipate that this trend will continue.
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To determine whether subthreshold symptoms of depression and anxiety mediated the associations found between chronic diseases, pain and recurrence of depression or anxiety, we conducted mediation analyses, through the indirect method by Preacher and Hayes involving bootstrapping approximations [ 45].
Since the CCHS follows a complicated multi-stage survey design, the re-sampling method involved in bootstrapping ensures that the best calculation of the variance between estimates is made [ 27].
The other three methods involved 100 bootstrap replicates, yielding strict consensus trees.
We accomplished this using a bootstrap method involving resampling n samples from the ground plot data with replacement using equal probability sampling, following recommendations from McRoberts et al. (2011) and based on work by Efron and Tibshirani (1986).
Many popular methods involve guessing.
The other methods involve scoring a goal.
One simulated data set is inadequate to reflect a null distribution and the bootstrap method involved in the approach of Li (2005) is computationally intensive.
This method involved building a set of regression trees based on bootstrapped samples of the belowground C data.
The offset method involves double printing.
This method involves adding polypropylene fibres.
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