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)

Value

statistics: Statistics of the model
parameters: Design parameters
means: Statistical summary of the study variable
rank: rank table of the study variable
comparison: Comparison between treatments
groups: Formation of treatment groups

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

Author

Felipe de Mendiburu

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

Examples

Run this code

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")
plot(out)

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