RVAideMemoire (version 0.9-27)

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

Description

Perform 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

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).

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)