agricolae (version 1.2-6)

durbin.test: Durbin test and multiple comparison of treatments

Description

A multiple comparison of the Durbin test for the balanced incomplete blocks for sensorial or categorical evaluation. It forms groups according to the demanded ones for level of significance (alpha); by default, 0.05.

Usage

durbin.test(judge, trt, evaluation, alpha = 0.05, group =TRUE, 
main = NULL, console=FALSE)

Arguments

judge

Identification of the judge in the evaluation

trt

Treatments

evaluation

variable

alpha

level of significant

group

TRUE or FALSE

main

Title

console

logical, print output

Value

juege

Vector, numeric

trt

Vector, numeric

evaluation

Vector, numeric

alpha

Vector, numeric, default is 0.05

group

Logic

main

text

Details

The post hoc test is using the criterium Fisher's least significant difference.

References

Practical Nonparametrics Statistics. W.J. Conover, 1999 Nonparametric Statistical Methods. Myles Hollander and Douglas A. Wofe, 1999

See Also

kruskal, friedman,BIB.test

Examples

# NOT RUN {
library(agricolae)
# Example 1. Conover, pag 391
person<-gl(7,3)
variety<-c(1,2,4,2,3,5,3,4,6,4,5,7,1,5,6,2,6,7,1,3,7)
preference<-c(2,3,1,3,1,2,2,1,3,1,2,3,3,1,2,3,1,2,3,1,2)
out<-durbin.test(person,variety,preference,group=TRUE,console=TRUE,
main="Seven varieties of ice cream manufacturer")
#startgraph
bar.group(out$groups,horiz=TRUE,xlim=c(0,10),density=4,las=1)
#endgraph
# Example 2. Myles Hollander, pag 311
# Source: W. Moore and C.I. Bliss. 1942
day<-gl(7,3)
chemical<-c("A","B","D","A","C","E","C","D","G","A","F","G","B","C","F",
 "B","E","G","D","E","F")
toxic<-c(0.465,0.343,0.396,0.602,0.873,0.634,0.875,0.325,0.330,0.423,0.987,
0.426,0.652,1.142,0.989,0.536,0.409,0.309,0.609,0.417,0.931)
out<-durbin.test(day,chemical,toxic,group=TRUE,console=TRUE,
main="Logarithm of Toxic Dosages")
# }