posthoc.kruskal.nemenyi.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. These tests are sometimes referred to as Nemenyi-tests for multiple comparisons of (mean) rank sums of independent samples.

Usage

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

## Default S3 method:
posthoc.kruskal.nemenyi.test( x, g, dist =
c("Tukey", "Chisquare"), ...)

## S3 method for class 'formula'
posthoc.kruskal.nemenyi.test(formula, data, subset,
na.action, dist =
c("Tukey", "Chisquare"), ...)

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").

...

further arguments to be passed to or from methods.

dist

the method for determining the p-value. The default distribution is "Tukey", else "Chisq".

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 Nemenyi 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 p-value according to the studentized range distribution.

statistic

The estimated upper quantile of the studentized range distribution. (or quantile of Chisq distribution)

p.adjust.method

Defaults to "none"

Note

Only for method = "Chisq" a tie correction is employed.

Author(s)

Thorsten Pohlert

References

Lothar Sachs (1997), Angewandte Statistik. Berlin: Springer. Pages: 395-397, 662-664.

See Also

kruskal.test, friedman.test, posthoc.friedman.nemenyi.test, Tukey, Chisquare

Examples

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