cor.2comp: Comparison of 2 Pearson's linear correlation coefficients

Description

Performs the test for equality of 2 Pearson's correlation coefficients. If the difference is not significant, the function returns the common coefficient, its confidence interval and performs the test for equality to a given value.

Usage

cor.2comp(var1, var2, var3, var4, alpha = 0.05, conf.level = 0.95, theo = 0)

Value

method.test: a character string giving the name of the global test computed.
data.name: a character string giving the name(s) of the data.
statistic: test statistics.
p.value: p-value for comparison of the 2 coefficients.
null.value: the value of the difference in coefficients under the null hypothesis, always 0.
alternative: a character string describing the alternative hypothesis.
estimate: the estimated correlation coefficients.
alpha: significance level.
conf.level: confidence level.
common.name: a character string explaining the elements of the table below.
common: data frame of results if the coefficients are not significantly different (common coefficient).

Arguments

var1: numeric vector (first variable of the first correlation).
var2: numeric vector (second variable of the first correlation).
var3: numeric vector (first variable of the second correlation).
var4: numeric vector (second variable of the second correlation).
alpha: significance level.
conf.level: confidence level.
theo: theoretical coefficient.

Author

Maxime HERVE <maxime.herve@univ-rennes1.fr>

Examples

Run this code

cor1.var1 <- 1:30+rnorm(30,0,2)
cor1.var2 <- 1:30+rnorm(30,0,3)
cor2.var1 <- (-1):-30+rnorm(30,0,2)
cor2.var2 <- (-1):-30+rnorm(30,0,3)
cor.2comp(cor1.var1,cor1.var2,cor2.var1,cor2.var2)