friedman: Friedman test and multiple comparison of treatments

View source: R/friedman.R

friedmanR 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

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