PASWR2 (version 1.0.5)

wilcoxe.test: Wilcoxon Exact Test

Description

Performs exact one sample and two sample Wilcoxon tests on vectors of data

Usage

wilcoxe.test(
  x,
  y = NULL,
  mu = 0,
  paired = FALSE,
  alternative = c("two.sided", "less", "greater"),
  conf.level = 0.95
)

Arguments

x

is a numeric vector of data values. Non-finite (i.e. infinite or missing) values will be omitted.

y

an optional numeric vector of data values

mu

a number specifying an optional parameter used to form the null hypothesis

paired

a logical indicating whether you want a paired test

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "less", or "greater". You can specify just the initial letter.

conf.level

confidence level of the interval

Value

A list of class htest, containing the following components:

statistic

the value of the test statistic with a name describing it

p.value

the p-value for the test

null.value

the location parameter mu

alternative

a character string describing the alternative hypothesis

method

the type of test applied

data.name

a character string giving the names of the data

conf.int

a confidence interval for the location parameter

estimate

an estimate of the location parameter

Details

If only x is given, or if both x and y are given and paired = TRUE, a Wilcoxon signed rank test of the null hypothesis that the distribution of x (in the one sample case) or of x - y (in the paired two sample case) is symmetric about mu is performed.

Otherwise, if both x and y are given and paired = FALSE, a Wilcoxon rank sum test is done. In this case, the null hypothesis is that the distribution of x and y differ by a location shift mu, and the alternative is that they differ by some other location shift (and the one-sided alternative "greater" is that x is shifted to the right of y).

References

• Gibbons, J.D. and Chakraborti, S. 1992. Nonparametric Statistical Inference. Marcel Dekker Inc., New York.

• Hollander, M. and Wolfe, D.A. 1999. Nonparametric Statistical Methods. New York: John Wiley & Sons.

See Also

wilcox.test

Examples

# NOT RUN {
 
# Wilcoxon Signed Rank Test
PH <- c(7.2, 7.3, 7.3, 7.4)
wilcoxe.test(PH, mu = 7.25, alternative = "greater")
# Wilcoxon Signed Rank Test (Dependent Samples)
with(data = AGGRESSION, 
wilcoxe.test(violence, noviolence, paired = TRUE, alternative = "greater"))
# Wilcoxon Rank Sum Test
x <- c(7.2, 7.2, 7.3, 7.3)
y <- c(7.3, 7.3, 7.4, 7.4)
wilcoxe.test(x, y)
rm(PH, x, y)
 
# }