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agricolae (version 1.1-5)

order.group: Ordering the treatments according to the multiple comparison

Description

This function allows us to compare the treatments averages or the adding of their ranges with the minimal significant difference which can vary from one comparison to another one. This function is used by the HSD, LSD, Kruskal-Wallis, Friedman or Durbin procedures.

Usage

order.group(trt, means, N, MSerror, Tprob, std.err, parameter=1, snk=0, 
DFerror=NULL,alpha=NULL,sdtdif=NULL,vartau=NULL,console)

Arguments

trt
Treatments
means
Means of treatment
N
Replications
MSerror
Mean square error
Tprob
minimum value for the comparison
std.err
standard error
parameter
Constante 1 (Sd), 0.5 (Sx)
snk
Constante = 1 (Student Newman Keuls)
DFerror
Degrees of freedom of the experimental error
alpha
Level of risk for the test
sdtdif
standar deviation of difference in BIB
vartau
matrix var-cov in PBIB
console
logical, print output

Value

  • trtFactor
  • meansNumeric
  • NNumeric
  • MSerrorNumeric
  • Tprobvalue between 0 and 1
  • std.errNumeric
  • parameterConstant
  • snkConstant
  • DFerrorNumeric
  • alphaNumeric
  • sdtdifNumeric
  • vartauNumeric, matrix

See Also

order.stat

Examples

Run this code
library(agricolae)
treatments <- c("A","B","C","D","E","F")
means<-c(20,40,35,72,49,58)
std.err<-c(1.2, 2, 1.5, 2.4, 1, 3.1)
minimun<-c(15,38,30,68,43,54)
maximun<-c(23,45,39,76,53,61)
replications <- c(4,4,3,4,3,3)
MSerror <- 55.8
value.t <- 2.1314
groups<-order.group(treatments,means,replications,MSerror,value.t,std.err,console=TRUE)
Means<-data.frame(treatments,means,std.err,r=replications,Min.= minimun,
Max.=maximun)
rownames(Means)<-Means[,1]
Means<-Means[,-1]
par(mfrow=c(2,2))
bar.group(groups,ylim=c(0,80))
bar.err(Means,variation="SE", bar=FALSE,col="green",ylim=c(0,80),
main="Standard error")
bar.err(Means,variation="SE", bar=FALSE,col=colors()[15],ylim=c(0,80),
main="Standard error",)
out<-bar.err(Means,variation="range", bar=FALSE,col=colors()[25],ylim=c(0,80),
space=2,main="Range")
points(out$index,out$means,pch=17,col="orange",cex=2)

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