posthoc.kruskal.dunn.test: Pairwise Test for Multiple Comparisons of Mean Rank Sums...

Description Usage Arguments Details Value Note Author(s) References See Also Examples

Description

Calculate pairwise multiple comparisons between group levels according to Dunn.

Usage

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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 NAs. 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.

See Also

kruskal.test, friedman.test, posthoc.friedman.nemenyi.test, pnorm, p.adjust

Examples

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##
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")


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