cor.diff.test: Calculate the p-value for differences in correlation... In brainGraph: Graph Theory Analysis of Brain MRI Data

Description

Given two sets of correlation coefficients and sample sizes, this function calculates and returns the z-scores and p-values associated with the difference between correlation coefficients. This function was adapted from http://stackoverflow.com/a/14519007/3357706.

Usage

 `1` ```cor.diff.test(r1, r2, n1, n2, alternative = c("two.sided", "less", "greater")) ```

Arguments

 `r1` Numeric (vector or matrix) of correlation coefficients, group 1 `r2` Numeric (vector or matrix) of correlation coefficients, group 2 `n1` Integer; number of observations, group 1 `n2` Integer; number of observations, group 2 `alternative` Character string specifying the alternative hypothesis test to use; one of: 'two.sided' (default), 'less', 'greater'

Value

A list containing:

 `p` The p-values `z` The z-score for the difference in correlation coefficients

Author(s)

Christopher G. Watson, [email protected]

Other Matrix functions: `apply_thresholds`, `create_mats`, `symmetrize_mats`
 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```## Not run: kNumSubjs <- summary(covars\$Group) corr.diffs <- cor.diff.test(corrs[[1]][[1]]\$R, corrs[[2]][[1]]\$R, kNumSubjs[1], kNumSubjs[2], alternative='two.sided') edge.diffs <- t(sapply(which(corr.diffs\$p < .05), function(x) mapply('[[', dimnames(corr.diffs\$p), arrayInd(x, dim(corr.diffs\$p))) )) ## End(Not run) ```