# fisher_transfer_test: Test for equal correlation In corTest: Robust Tests 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

 `1` ```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 <dyu33@jhu.edu>, Weiliang Qiu <weiliang.qiu@gmail.com>

## 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

 ```1 2 3 4 5 6``` ```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) ```

corTest documentation built on Nov. 16, 2020, 9:15 a.m.