brunner.munzel.test: Brunner-Munzel Test for Stochastic Equality

In gel-research-group/lawstat: Tools for Biostatistics, Public Policy, and Law

Description

The Brunner–Munzel test for stochastic equality of two samples, which is also known as the Generalized Wilcoxon test. NAs from the data are omitted.

Usage

brunner.munzel.test(
  x,
  y,
  alternative = c("two.sided", "greater", "less"),
  alpha = 0.05
)

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.
alpha	significance level, default is 0.05 for 95% confidence interval.

Details

There exist discrepancies with \insertCiteBrunner_Munzel_2000;textuallawstat because there is a typo in the paper. The corrected version is in \insertCiteNeubert_Brunner_2007;textuallawstat (e.g., compare the estimates for the case study on pain scores). The current function follows \insertCiteNeubert_Brunner_2007;textuallawstat.

Value

A list of class "htest" with the following components:

statistic	the Brunner–Munzel test statistic.
parameter	the degrees of freedom.
conf.int	the confidence interval.
p.value	the p-value of the test.
data.name	a character string giving the name of the data.
estimate	an estimate of the effect size, i.e., P(X < Y) + 0.5 P(X =Y ).

Author(s)

Wallace Hui, Yulia R. Gel, Joseph L. Gastwirth, Weiwen Miao. This function was updated with the help of Dr. Ian Fellows.

References

\insertAllCited

See Also

wilcox.test, pwilcox

Examples

## Pain score on the third day after surgery for 14 patients under
## the treatment Y and 11 patients under the treatment N
## (see Brunner and Munzel, 2000; Neubert and Brunner, 2007).

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
## 95 percent confidence interval:
##  0.5952169 0.9827052
## sample estimates:
## P(X<Y)+.5*P(X=Y)
##        0.788961

gel-research-group/lawstat documentation built on Dec. 20, 2021, 9:50 a.m.