compar_r_fisher: Compare two correlation coefficients obtained from different...

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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)

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

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

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.

Author(s)

P. Savary

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)

graph4lg documentation built on Feb. 16, 2023, 5:43 p.m.