R: Ordering the treatments according to the multiple comparison

order.group {agricolae} | R Documentation

## 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` | standard deviation of difference in BIB
`vartau` | matrix var-cov in PBIB
`console` | logical, print output

### Value

`trt` | Factor
`means` | Numeric
`N` | Numeric
`MSerror` | Numeric
`Tprob` | value between 0 and 1
`std.err` | Numeric
`parameter` | Constant
`snk` | Constant
`DFerror` | Numeric
`alpha` | Numeric
`sdtdif` | Numeric
`vartau` | Numeric, matrix

### Author(s)

Felipe de Mendiburu

### See Also

`order.stat`

### Examples

    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="SD", bar=FALSE,col="green",ylim=c(0,80),
    main="Standard deviation")
    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)

[Package agricolae version 1.2-6 Index]