R: Multiple comparisons: Tukey

HSD.test {agricolae} | R Documentation

## Multiple comparisons: Tukey

### Description

It makes multiple comparisons of treatments by means of Tukey. The level by alpha default is 0.05.

### Usage

    HSD.test(y, trt, DFerror, MSerror, alpha = 0.05, group=TRUE, main = NULL,console=FALSE)

### Arguments

`y` | model(aov or lm) or answer of the experimental unit
`trt` | Constant( only y=model) or vector treatment applied to each experimental unit
`DFerror` | Degree free
`MSerror` | Mean Square Error
`alpha` | Significant level
`group` | TRUE or FALSE
`main` | Title
`console` | logical, print output

### Details

It is necessary first makes a analysis of variance.

### Value

`y` | class (aov or lm) or vector numeric
`trt` | constant (only y=model) or vector alfanumeric
`DFerror` | Numeric
`MSerror` | Numeric
`alpha` | Numeric
`group` | Logic
`main` | Text

### Author(s)

Felipe de Mendiburu

### References

1. Principles and procedures of statistics a biometrical approach Steel & Torry & Dickey. Third Edition 1997 2. Multiple comparisons theory and methods. Departament of statistics the Ohio State University. USA, 1996. Jason C. Hsu. Chapman Hall/CRC.

### See Also

`LSD.test`, `waller.test` , `SNK.test` , `duncan.test`

### Examples

    library(agricolae)
    data(sweetpotato)
    model<-aov(yield~virus, data=sweetpotato)
    out <- HSD.test(model,"virus", group=TRUE,console=TRUE,
    main="Yield of sweetpotato\nDealt with different virus")
    #stargraph
    bar.group(out$groups,ylim=c(0,45),density=4,border="blue")
    #endgraph
    out<-HSD.test(model,"virus", group=FALSE)
    means<-out$means
    # Old version HSD.test()
    df<-df.residual(model)
    MSerror<-deviance(model)/df
    with(sweetpotato,HSD.test(yield,virus,df,MSerror, group=TRUE,console=TRUE,
    main="Yield of sweetpotato. Dealt with different virus"))

[Package agricolae version 1.2-6 Index]