friedman: 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)

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

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

Author

Felipe de Mendiburu

Details

The post hoc friedman test is using the criterium Fisher's least significant difference (LSD)

References

Practical Nonparametrics Statistics. W.J. Conover, 1999

Examples

Run this code

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

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