| kruskal {agricolae} | R Documentation |
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"))