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

posthoc.kruskal.nemenyi.test {PMCMR} | R Documentation

## Pairwise Test for Multiple Comparisons of Mean Rank Sums (Nemenyi-Tests)

### 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

    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 `NA`s. 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

    ##
    require(stats)
    data(InsectSprays)
    attach(InsectSprays)
    kruskal.test(count, spray)
    posthoc.kruskal.nemenyi.test(count, spray)
    posthoc.kruskal.nemenyi.test(count, spray, "Chisq")
    detach(InsectSprays)
    rm(InsectSprays)
    ## Formula Interface
    posthoc.kruskal.nemenyi.test(count ~ spray, data = InsectSprays, dist="Tukey")

[Package PMCMR version 4.2 Index]