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.

### See Also

`kruskal.test`, `vanWaerden.test`, `posthoc.kruskal.nemenyi.test`, `posthoc.kruskal.dunn.test`, `TDist`, `p.adjust`

### Examples

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

[Package PMCMR version 4.2 Index]