R: Pairwise post-hoc Test for Multiple Comparisons of Rank Sums...

posthoc.friedman.conover.test {PMCMR} | R Documentation

## Pairwise post-hoc Test for Multiple Comparisons of Rank Sums for Unreplicated Blocked Data (Conover-Test)

### Description

Calculate pairwise comparisons using Conover post-hoc test for unreplicated blocked data. This test is usually conducted post-hoc after significant results of the `friedman.test`. The statistics refer to the student-t-distribution (`TDist`).

### Usage

    posthoc.friedman.conover.test(y, ...)

    ## Default S3 method:
     posthoc.friedman.conover.test(y, groups, blocks,
    p.adjust.method = p.adjust.methods, ...)

### Arguments

`y` | either a numeric vector of data values, or a data matrix.
`groups` | a vector giving the group for the corresponding elements of `y` if this is a vector; ignored if `y` is a matrix. If not a factor object, it is coerced to one.
`blocks` | a vector giving the block for the corresponding elements of `y` if this is a vector; ignored if `y` is a matrix. If not a factor object, it is coerced to one.

`p.adjust.method` | Method for adjusting p values (see `p.adjust`).
`...` | further arguments to be passed to or from methods.

### Details

A one-way ANOVA with repeated measures that is also referred to as ANOVA with unreplicated block design can also be conducted via the `friedman.test`. The consequent post-hoc pairwise multiple comparison test according to Conover is conducted with this function.

If y is a matrix, than the columns refer to the treatment and the rows indicate the block.

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 according to the student-t-distribution.
`statistic` | The estimated quantiles of the student-t-distribution.
`p.adjust.method` | The applied method for p-value adjustment.

### Note

This function does not test for ties.

### 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.

W. J. Conover (1999), Practical nonparametric Statistics, 3rd. Edition, Wiley.

### See Also

`friedman.test`, `posthoc.friedman.nemenyi.test`, `TDist` `p.adjust`

### Examples

    ##
    ## Sachs, 1997, p. 675
    ## Six persons (block) received six different diuretics
    ## (A to F, treatment).
    ## The responses are the Na-concentration (mval)
    ## in the urine measured 2 hours after each treatment.
    ##
    y <- matrix(c(
    3.88, 5.64, 5.76, 4.25, 5.91, 4.33, 30.58, 30.14, 16.92,
    23.19, 26.74, 10.91, 25.24, 33.52, 25.45, 18.85, 20.45,
    26.67, 4.44, 7.94, 4.04, 4.4, 4.23, 4.36, 29.41, 30.72,
    32.92, 28.23, 23.35, 12, 38.87, 33.12, 39.15, 28.06, 38.23,
    26.65),nrow=6, ncol=6,
    dimnames=list(1:6,c("A","B","C","D","E","F")))
    print(y)
    friedman.test(y)
    posthoc.friedman.conover.test(y=y, p.adjust="none")

[Package PMCMR version 4.2 Index]