R: Many multi-sample tests

Many non parametric multi-sample tests {Rfast} | R Documentation

## Many multi-sample tests

### Description

Many multi-sample tests.

### Usage

    kruskaltests(x, ina, logged = FALSE)
    cqtests(x, treat, block, logged = FALSE)

### Arguments

`x` | A matrix with the data, where the rows denote the samples (and the two groups) and the columns are the variables.
`ina` | A numerical vector with 1s, 2s, 3s and so one indicating the two groups. Be careful, the function is desinged to accept numbers greater than zero.
`treat` | In the case of the Cochran's Q test, this argument plays the role of the "ina" argument.
`block` | This item denotes the subjects which are the same. Similarly to "ina" a numeric vector with 1s, 2s, 3s and so on.
`logged` | Should the p-values be returned (FALSE) or their logarithm (TRUE)?

### Details

The "kruskaltests" performs the Kruskal-Wallis non parametric alternative to analysis of variance test. The "cqtests" performs the Cocrhan's Q test for the equality of more than two groups whose values are strictly binary (0 or 1). This is a generalisation of the McNemar's test in the multi-sample case.

### Value

A matrix with the test statistic and the p-value of each test.

### Author(s)

Michail Tsagris

R implementation and documentation: Michail Tsagris <mtsagris@yahoo.gr> and Manos Papadakis <papadakm95@gmail.com>.

### See Also

`block.anovas, ftests`

### Examples

    x <- matrix( rexp(300 * 200), ncol = 200 )
    ina <- rbinom(300, 3, 0.6) + 1
    system.time( kruskaltests(x, ina) )
    x <- matrix( rbinom(300 * 200, 1, 0.6), ncol = 200 )
    treat <- rep(1:3, each = 100)
    block <- rep(1:3, 100)
    system.time( cqtests(x, treat, block) )
    x <- NULL

[Package Rfast version 2.0.0 Index]