cor_test: Correlation significance testing using Fisher's...

In Rfast2: A Collection of Efficient and Extremely Fast R Functions II

Correlation significance testing using Fisher's z-transformation

Description

Correlation significance testing using Fisher's z-transformation.

Usage

cor_test(y, x, type = "pearson", rho = 0, a = 0.05 )

Arguments

y	A numerical vector.
x	A numerical vector.
type	The type of correlation you want. "pearson" and "spearman" are the two supported types because their standard error is easily calculated.
rho	The value of the hypothesised correlation to be used in the hypothesis testing.
a	The significance level used for the confidence intervals.

Details

The function uses the built-in function "cor" which is very fast, then computes a confidence interval and produces a p-value for the hypothesis test.

Value

A vector with 5 numbers; the correlation, the p-value for the hypothesis test that each of them is equal to "rho", the test statistic and the a/2\% lower and upper confidence limits.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail].

See Also

allbetas, univglms

Examples

x <- rcauchy(60)
y <- rnorm(60)
cor_test(y, x)  

Rfast2 documentation built on Aug. 8, 2023, 1:11 a.m.