cor.multcomp: Comparison of Pearson's linear correlation coefficients

Description

Perform comparisons of Pearson's linear correlation coefficients. If no difference, the function returns the common correlation coefficient, its confidence interval and test for its equality to a given value. If difference is significative, the functions performs pairwise comparisons between coefficients.

Usage

cor.multcomp(var1, var2, fact, alpha = 0.05, conf.level = 0.95, theo = 0, p.method = "fdr")

Arguments

var1

numeric vector (first variable).

var2

numeric vector (second variable).

fact

factor (groups).

alpha

significance level.

conf.level

confidence level.

theo

theoretical coefficient.

p.method

method for p-values correction. See help of the p.adjust() function.

Value

levelsnumber of levels of fact.
conf.levelconfidence level.
alphasignificance level.
coeffsobserved correlation coefficients.
chi2.comptest statistics for equality of all coefficients.
p.compp-value for equality of all coefficients.
compdata frame of results for equality of all coefficients.
r.commcommon correlation coefficient.
r.theotheoretical coefficient.
u.commtest statistics for equality of the common coefficient to the theoretical value.
p.commp-value for equality of the common coefficient to the theoretical value.
commdata frame for equality of the common coefficient to the theoretical value.
p.methodmethod for p-values correction.
u.multcomptest statistics of pairwise comparisons.
p.multcompp-values of pairwise comparisons.
multcompdata frame of results of pairwise comparisons.

Examples

Run this code

var1<-c(1:15+rnorm(15,0,4),1:15+rnorm(15,0,1),1:15+rnorm(15,0,8))
var2<-c(-1:-15+rnorm(15,0,4),1:15+rnorm(15,0,1),1:15+rnorm(15,0,8))
factor<-factor(rep(LETTERS[1:3],each=15))
cor.multcomp(var1,var2,factor)

var3<-c(1:15+rnorm(15,0,1),1:15+rnorm(15,0,3),1:15+rnorm(15,0,2))
cor.multcomp(var1,var3,factor)

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