kruskal: Kruskal Wallis test and multiple comparison of treatments.

In agricolae: Statistical Procedures for Agricultural Research

Kruskal Wallis test and multiple comparison of treatments.

Description

It makes the multiple comparison with Kruskal-Wallis. The alpha parameter by default is 0.05. Post hoc test is using the criterium Fisher's least significant difference. The adjustment methods include the Bonferroni correction and others.

Usage

kruskal(y, trt, alpha = 0.05, p.adj=c("none","holm","hommel", 
"hochberg", "bonferroni", "BH", "BY", "fdr"), group=TRUE, main = NULL,console=FALSE)

Arguments

y	response
trt	treatment
alpha	level signification
p.adj	Method for adjusting p values (see p.adjust)
group	TRUE or FALSE
main	Title
console	logical, print output

Details

For equal or different repetition.
For the adjustment methods, see the function p.adjusted.
p-adj = "none" is t-student.

Value

statistics	Statistics of the model
parameters	Design parameters
means	Statistical summary of the study variable
comparison	Comparison between treatments
groups	Formation of treatment groups

Author(s)

Felipe de Mendiburu

References

Practical Nonparametrics Statistics. W.J. Conover, 1999

See Also

BIB.test, DAU.test, duncan.test, durbin.test, friedman, HSD.test, LSD.test, Median.test, PBIB.test, REGW.test, scheffe.test, SNK.test, waerden.test, waller.test, plot.group

Examples

library(agricolae)
data(corn)
str(corn)
comparison<-with(corn,kruskal(observation,method,group=TRUE, main="corn"))
comparison<-with(corn,kruskal(observation,method,p.adj="bon",group=FALSE, main="corn"))

agricolae documentation built on Oct. 23, 2023, 1:06 a.m.