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

In RVAideMemoire: Testing and Plotting Procedures for Biostatistics

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)

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 HERVE <[e-mail]>

See Also

cor.test

Examples

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)

RVAideMemoire documentation built on Nov. 6, 2023, 5:07 p.m.