graph4lg (version 1.8.0)

compar_r_fisher: Compare two correlation coefficients obtained from different sample sizes

Description

The function compares two correlation coefficients obtained from different sample sizes using Z-Fisher transformation.

Usage

compar_r_fisher(data)

Value

An object of class data.frame with the same columns as 'data' and 4 columns more : z1, z2 (respective z-scores), Z (test's statistic) and p (p-value) of the test.

Arguments

data

An object of class data.frame with at least 4 columns of data used to perform the test. 4 columns must be called "n1", "n2", "r1" and "r2".

• n1 and n2 are the sizes of the samples from which r1 and r2 were computed respectively.

• r1 and r2 are Pearson's correlation coefficients

Author

P. Savary

Details

The Z-Fisher method consists in computing z scores from the correlation coefficients and to compare these z scores. z scores are computed as follows : Let n1 and r1 be the sample size and the correlation coefficient, z1 = (1/2)*log( (1+r1) / (1-r1) ) Then, a test's statistic is computed from z1 and z2 : Z = (z1-z2) / sqrt( (1/(n1-3)) + (1/(n2-3))) If Z is above the limit given by the alpha value, then the difference between r1 and r2 is significant

Examples

df <- data.frame(n1 = rpois(n = 40, lambda = 85),
                 n2 = rpois(n = 40, lambda = 60),
                 r1 = runif(n = 40, min = 0.6, max = 0.85),
                 r2 = runif(n = 40, min = 0.55, max = 0.75))
data <- compar_r_fisher(df)