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

Description

Calculate pairwise multiple comparisons between group levels according to Dunn.

Usage

 ```1 2 3 4 5 6 7 8 9``` ```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 `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 Kruskal-Wallis-Test `kruskal.test` can be employed that is also referred to as the Kruskal<e2><80><93>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).

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.

`kruskal.test`, `friedman.test`, `posthoc.friedman.nemenyi.test`, `pnorm`, `p.adjust`
 ``` 1 2 3 4 5 6 7 8 9 10``` ```## 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") ```