Test the difference between two correlations.

Usage

cor_diff(r1, n1, r2, n2, n = NULL, rcov = NULL)

Arguments

r1, r2

Correlation coefficients (Pearson's r).

n, n1, n2

Sample sizes.

rcov

[Optional] Only for nonindependent rs:

r1 is r(X,Y),

r2 is r(X,Z),

then, as Y and Z are also correlated,

we should also consider rcov: r(Y,Z)

Value

Invisibly return the p value.

Examples

# two independent rs (X~Y vs. Z~W)
cor_diff(r1=0.20, n1=100, r2=0.45, n2=100)
#> r1 = 0.200 (N = 100)
#> r2 = 0.450 (N = 100)
#> Difference of correlation: z = -1.96, p = 0.050 *  

# two nonindependent rs (X~Y vs. X~Z, with Y and Z also correlated [rcov])
cor_diff(r1=0.20, r2=0.45, n=100, rcov=0.80)
#> r1 = 0.200
#> r2 = 0.450
#> (N = 100, r_cov = 0.800)
#> Difference of correlation: t(97) = -4.56, p = 1e-05 ***