kruskaltests: Many multi-sample tests

In Rfast: A Collection of Efficient and Extremely Fast R Functions

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 <[e-mail]> and Manos Papadakis <[e-mail]>.

See Also

block.anovas, ftests

Examples

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

Rfast documentation built on Nov. 9, 2023, 5:06 p.m.