R: Pairwise Test for Multiple Comparisons of normal scores (van...

posthoc.vanWaerden.test {PMCMR}

R Documentation

Pairwise Test for Multiple Comparisons of normal scores (van der Waerden test)

Description

Calculate pairwise multiple comparisons between group levels according to van der Waerden.

Usage

posthoc.vanWaerden.test(x, ...)

## Default S3 method:
posthoc.vanWaerden.test( x, g, p.adjust.method =
p.adjust.methods, ...)

## S3 method for class 'formula'
posthoc.vanWaerden.test(formula, data, subset,
na.action, p.adjust.method = p.adjust.methods, ...)

Arguments

`x`	a numeric vector of data values, or a list of numeric data vectors.
`g`	a vector or factor object giving the group for the corresponding elements of `x`. Ignored if `x` is a list.
`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 `NA`s. Defaults to `getOption("na.action")`.
`p.adjust.method`	Method for adjusting p values (see `p.adjust`).
`...`	further arguments to be passed to or from methods.

Details

For one-factorial designs with samples that do not meet the assumptions for one-way-ANOVA and subsequent post-hoc tests, the van der Waerden test vanWaerden.test using normal scores can be employed. Provided that significant differences were detected by this global test, one may be interested in applying post-hoc tests according to van der Waerden for pairwise multiple comparisons of the group levels.

First, the data are ranked according to Kruskal-Wallis. Second, the ranks are transformed to normal scores. The group means of normal scores and the total variance is used to calculate quantiles of the student-t-distribution and consequent p-values.

See vignette("PMCMR") for details.

Value

A list with class "PMCMR"

`method`	The applied method.
`data.name`	The name of the data.
`p.value`	The two-sided p-value of the student-t-distribution.
`statistic`	The estimated quantile of the student-t-distribution.
`p.adjust.method`	The applied method for p-value adjustment.

Note

There is no tie correction applied in this function.

Author(s)

Thorsten Pohlert

References

W. J. Conover and R. L. Iman (1979), On multiple-comparisons procedures, Tech. Rep. LA-7677-MS, Los Alamos Scientific Laboratory.

Examples

##
require(stats) 
data(InsectSprays)
attach(InsectSprays)
vanWaerden.test(count, spray)
posthoc.vanWaerden.test(count, spray, "bonferroni")
detach(InsectSprays)
rm(InsectSprays)

[Package PMCMR version 4.3 Index]