agricolae (version 1.2-8)

kruskal: 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

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

Details

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

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

# NOT RUN {
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"))
# }