durbin.test | R Documentation |
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.
durbin.test(judge, trt, evaluation, alpha = 0.05, group =TRUE,
main = NULL, console=FALSE)
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 |
The post hoc test is using the criterium Fisher's least significant difference.
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 |
Felipe de Mendiburu
Practical Nonparametrics Statistics. W.J. Conover, 1999 Nonparametric Statistical Methods. Myles Hollander and Douglas A. Wofe, 1999
BIB.test
, DAU.test
, duncan.test
,
friedman
, HSD.test
, kruskal
,
LSD.test
, Median.test
, PBIB.test
,
REGW.test
, scheffe.test
, SNK.test
,
waerden.test
, waller.test
, plot.group
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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