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#' @param ranktransform If `TRUE`, will rank-transform the variables prior to |
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#' estimating the correlation, which is one way of making the analysis more |
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#' resistant to extreme values (outliers). Note that, for instance, a |
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#' Pearson's correlation on rank-transformed data is equivalent to a |
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#' Spearman's rank correlation. Thus, using `robust=TRUE` and |
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#' `method="spearman"` is redundant. Nonetheless, it is an easy option to |
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#' increase the robustness of the correlation as well as flexible way to |
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#' obtain Bayesian or multilevel Spearman-like rank correlations. |
We still refer to robust in the documentation, despite that this argument has been expanded and is now more specific (ranktransform and winsorize). Need to remove mentions of robust in favour of ranktransform
