brunner.munzel.test {lawstat}R Documentation

The Brunner-Munzel Test for Stochastic Equality

Description

This function performs the Brunner-Munzel test for stochastic equality of two samples.

Usage

brunner.munzel.test(x, y, alternative = c("two.sided", "greater", "less"))

Arguments

x the numeric vector of data values from the sample 1.
y the numeric vector of data values from the sample 2.
alternative a character string specifying the alternative hypothesis, must be one of 'two.sided' (default), 'greater' or 'less'. User can specify just the initial letter.

Value

A list containing the following components:

statistic the Brunner-Munzel test statistic.
parameter the degrees of freedom.
p.value the p-value of the test.
data.name a character string giving the name of the data.
alternative a character string describing the alternative hypothesis.

Author(s)

Wallace Hui, Yulia R. Gel, Joseph L. Gastwirth, Weiwen Miao

References

Brunner, E. and Munzel, U. (2000) The Nonparametric Behrens-Fisher Problem: Asymptotic Theory and a Small-Sample Approximation, Biometrical Journal 42, 17-25.

Reiczigel, J., Zakarias, I. and Rozsa, L. (2005) A Bootstrap Test of Stochastic Equality of Two Populations, The American Statistician 59, 1-6.

See Also

wilcox.test, pwilcox

Examples

## Pain score on the third day after surgery for 14 patients under
## the treatment \emph{Y} and 11 patients under the treatment \emph{N}
## (see Brunner and Munzel (2000))

Y<-c(1,2,1,1,1,1,1,1,1,1,2,4,1,1)
N<-c(3,3,4,3,1,2,3,1,1,5,4)

brunner.munzel.test(Y, N)

##       Brunner-Munzel Test
## data: Y and N
## Brunner-Munzel Test
## Statistic = 3.1375,  df = 17.683, p-value = 0.005786

[Package lawstat version 1.02 Index]