# perm.cor.test: Permutation Pearson's correlation test In RVAideMemoire: Testing and Plotting Procedures for Biostatistics

## Description

Performs a permutation Pearson's product-moment correlation test.

## Usage

 1 2 perm.cor.test(x, y, alternative = c("two.sided", "less", "greater"), nperm = 999, progress = TRUE)

## Arguments

 x, y numeric vectors of data values. x and y must have the same length. alternative a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". nperm number of permutations. progress logical indicating if the progress bar should be displayed.

## Details

The function deals with the limitted floating point precision, which can bias calculation of p-values based on a discrete test statistic distribution.

## Value

 method name of the test. data.name a character string giving the name(s) of the data. statistic test statistics of the parametric test. permutations number of permutations. p.value p-value of the permutation test. estimate the estimated correlation coefficient. alternative a character string describing the alternative hypothesis. null.value the value of the association measure under the null hypothesis, always 0.

## Author(s)

Maxime Herv<e9> <[email protected]>

## Examples

 1 2 3 x <- rnorm(50) y <- runif(50) perm.cor.test(x,y)

### Example output

*** Package RVAideMemoire v 0.9-68 ***

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Pearson's product-moment correlation - Permutation test

data:  x and y
999 permutations
t = -0.97854, p-value = 0.348
alternative hypothesis: true correlation is not equal to 0
sample estimates:
cor
-0.1398523

RVAideMemoire documentation built on May 14, 2018, 5:07 p.m.