agricolae (version 1.2-6)

HSD.test: 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

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

Details

It is necessary first makes a analysis of variance.

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

# NOT RUN {
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"))
# }