# Multiplicity Adjustment for Correlation Coefficient Confidence Intervals

Has anyone dealt with the issue of computing confidence intervals for the correlation coefficient (parametric or non-parametric) and having to include a multiplicity adjustment factor? I was wondering if this can be done using the bootstrap. Any R package for this purpose.

Instead of just adjusting $P$-values when testing a large number of correlation coefficients, one can use the bootstrap to compute confidence intervals for the ranks of all the correlations. For example, the apparently strongest $|r|$ over 100 coefficients may have a 0.95 bootstrap confidence interval for its rank of [1, 20], i.e. the data are consistent with that pair of variables being only the twentieth most strongly related pair as well as being the best.