PMCMRplus (version 1.3.0)

bwsKSampleTest: Murakami's k-Sample BWS Test

Description

Performs Murakami's k-Sample BWS Test.

Usage

bwsKSampleTest(x, ...)
# S3 method for default
bwsKSampleTest(x, g, nperm = 1000, ...)
# S3 method for formula
bwsKSampleTest(formula, data, subset, na.action,
  nperm = 1000, ...)

Arguments

x

a numeric vector of data values, or a list of numeric data vectors.

…

further arguments to be passed to or from methods.

g

a vector or factor object giving the group for the corresponding elements of "x". Ignored with a warning if "x" is a list.

nperm

number of permutations for the assymptotic permutation test. Defaults to 1000.

formula

a formula of the form response ~ group where response gives the data values and group a vector or factor of the corresponding groups.

data

an optional matrix or data frame (or similar: see model.frame) containing the variables in the formula formula. By default the variables are taken from environment(formula).

subset

an optional vector specifying a subset of observations to be used.

na.action

a function which indicates what should happen when the data contain NAs. Defaults to getOption("na.action").

Value

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

method

a character string indicating what type of test was performed.

data.name

a character string giving the name(s) of the data.

statistic

the estimated quantile of the test statistic.

p.value

the p-value for the test.

parameter

the parameters of the test statistic, if any.

alternative

a character string describing the alternative hypothesis.

estimates

the estimates, if any.

null.value

the estimate under the null hypothesis, if any.

Details

The null hypothesis, H\(_0: F_1 = F_2 = \ldots = F_k\) is tested against the alternative, H\(_\mathrm{A}: F_i \ne F_j ~~(i \ne j)\), with at least one unequality beeing strict.

The p-values are estimated through an assymptotic boot-strap method.

References

Baumgartner, W., Weiss, P., Schindler, H. (1998) A nonparametric test for the general two-sample problem, Biometrics 54, 1129--1135.

Murakami, H. (2006) K-sample rank test based on modified Baumgartner statistic and its power comparison, J. Jpn. Comp. Statist. 19, 1--13.

See Also

sample, bwsAllPairsTest, bwsManyOneTest.

Examples

# NOT RUN {
#' ## Hollander & Wolfe (1973), 116.
## Mucociliary efficiency from the rate of removal of dust in normal
## subjects, subjects with obstructive airway disease, and subjects
## with asbestosis.
x <- c(2.9, 3.0, 2.5, 2.6, 3.2) # normal subjects
y <- c(3.8, 2.7, 4.0, 2.4)      # with obstructive airway disease
z <- c(2.8, 3.4, 3.7, 2.2, 2.0) # with asbestosis

datf <- data.frame(
  g = g <- c(rep("ns", length(x)), rep("oad",
      length(y)), rep("a", length(z))),
  x = x <- c(x, y, z))

## k-sample BWS Test
bwsKSampleTest(x ~ g, datf)

# }