R: Pairwise Test for Multiple Comparisons of Mean Rank Sums...

posthoc.kruskal.dunn.test {PMCMR}

R Documentation

Pairwise Test for Multiple Comparisons of Mean Rank Sums (Dunn's-Test)

Description

Calculate pairwise multiple comparisons between group levels according to Dunn.

Usage

posthoc.kruskal.dunn.test(x, ...)

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

## S3 method for class 'formula'
posthoc.kruskal.dunn.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 Kruskal-Wallis-Test kruskal.test can be employed that is also referred to as the Kruskal–Wallis one-way analysis of variance by ranks. Provided that significant differences were detected by this global test, one may be interested in applying post-hoc tests according to Dunn for pairwise multiple comparisons of the ranked data.

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 standard normal distribution.
`statistic`	The estimated quantile of the standard normal distribution.
`p.adjust.method`	The applied method for p-value adjustment.

Note

A tie correction will be employed according to Glantz (2012).

Author(s)

Thorsten Pohlert

References

O.J. Dunn (1964). Multiple comparisons using rank sums. Technometrics, 6, 241-252.

S. A. Glantz (2012), Primer of Biostatistics. New York: McGraw Hill.

Examples

##
require(stats) 
data(InsectSprays)
attach(InsectSprays)
kruskal.test(count, spray)
posthoc.kruskal.dunn.test(count, spray, "bonferroni")
detach(InsectSprays)
rm(InsectSprays)
## Formula Interface
posthoc.kruskal.dunn.test(count ~ spray, data = InsectSprays, p.adjust="bonf")

[Package PMCMR version 4.3 Index]