| friedman {agricolae} | R Documentation |
Friedman test and multiple comparison of treatments
Description
The data consist of b-blocks mutually independent k-variate random variables Xij, i=1,..,b; j=1,..k. The random variable X is in block i and is associated with treatment j. It makes the multiple comparison of the Friedman test with or without ties. A first result is obtained by friedman.test of R.
Usage
friedman(judge,trt,evaluation,alpha=0.05,group=TRUE,main=NULL,console=FALSE)
Arguments
judge |
Identification of the judge in the evaluation |
trt |
Treatment |
evaluation |
Variable |
alpha |
Significant test |
group |
TRUE or FALSE |
main |
Title |
console |
logical, print output |
Details
The post hoc friedman test is using the criterium Fisher's least significant difference (LSD)
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, HSD.test, kruskal,
LSD.test, Median.test, PBIB.test,
REGW.test, scheffe.test, SNK.test,
waerden.test, waller.test, plot.group
Examples
library(agricolae)
data(grass)
out<-with(grass,friedman(judge,trt, evaluation,alpha=0.05, group=TRUE,console=TRUE,
main="Data of the book of Conover"))
#startgraph
plot(out,variation="IQR")
#endgraph