Comparison of 2 Pearson's linear correlation coefficients

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Description

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

Usage

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

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.

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).

Author(s)

Maxime Herv<e9> <mx.herve@gmail.com>

See Also

cor.test

Examples

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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)

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