fisher_transfer_test {corTest}

Test for equal correlation

Description

Compute p-value with Fisher’s Z-transformation test. If biasCorrection is true, the corrected correlation is used. The formula is rho.corrected = rho - rho/(2*(n-1)).

Usage

fisher_transfer_test(x1, z1, x0, z0, biasCorrection = TRUE)

Arguments

x1

a numeric vector

z1

a numeric vector with same length as x1

x0

a numeric vector

z0

a numeric vector with same length as x0

biasCorrection

a boolean value

Value

p-value of test for testing if correlation between x1 and z1 is the same as that between x0 and z0

Author(s)

Danyang Yu <[e-mail]>, Weiliang Qiu <[e-mail]>

References

Danyang Yu, Zeyu Zhang, Kimberly Glass, Jessica Su, Dawn L. DeMeo, Kelan Tantisira, Scott T. Weiss, Weiliang Qiu(corresponding author). New Statistical Methods for Constructing Robust Differential Correlation Networks to characterize the interactions among microRNAs. Scientific Reports 9, Article number: 3499 (2019)

Examples

x1 = ghdist(n = 100, g = 0.2, h = 0.2)
x0 = ghdist(n = 100, g = 0.2, h = 0.2)
z1 = x1 + ghdist(n = 100, g = 0.2, h = 0.2)
z0 = x0 + ghdist(n = 100, g = 0.2, h = 0.2)
p = fisher_transfer_test(x1, z1, x0, z0)
print(p)