agricolae (version 1.1-4)

LSD.test: Multiple comparisons, "Least significant difference" and Adjust P-values

Description

Multiple comparisons of treatments by means of LSD and a grouping of treatments. The level by alpha default is 0.05. Returns p-values adjusted using one of several methods

Usage

LSD.test(y, trt, DFerror, MSerror, alpha = 0.05, p.adj=c("none","holm", 
"hochberg", "bonferroni", "BH", "BY", "fdr"), group=TRUE, main = NULL)

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

Degrees of freedom of the experimental error

MSerror

Means square error of the experimental

alpha

Level of risk for the test

p.adj

Method for adjusting p values (see p.adjust)

group

TRUE or FALSE

main

title of the study

Value

• y
  class (aov or lm) or vector numeric
• trt
  constant (only y=model) or vector alfanumeric
• DFerror
  Numeric
• MSerror
  Numeric
• alpha
  Numeric
• p.adj
  text, see p.adjust
• group
  Logic
• main
  Numeric

Details

For equal or different repetition. p.adj = "holm", "hochberg", "bonferroni", "BH", "BY", "fdr". see p.adjust() p-adj ="none" is t-student. p-adj ="hommel" is not applied in this test.

References

Steel, R.; Torri,J; Dickey, D.(1997) Principles and Procedures of Statistics A Biometrical Approach. pp178.

See Also

HSD.test, waller.test, SNK.test, bar.err, bar.group,duncan.test

Examples

library(agricolae)
data(sweetpotato)
model<-aov(yield~virus, data=sweetpotato)
out <- LSD.test(model,"virus", p.adj="bonferroni",
main="Yield of sweetpotato
dealt with different virus")
#stargraph
bar.group(out$groups,ylim=c(0,45),density=4,border="blue")
#endgraph
# Old version LSD.test()
attach(sweetpotato)
df<-df.residual(model)
MSerror<-deviance(model)/df
out <- LSD.test(yield,virus,df,MSerror, p.adj="bonferroni", group=FALSE,
main="Yield of sweetpotato
dealt with different virus")
detach(sweetpotato)
#stargraph
# Variation rank: Max. - Min.
bar.err(out$means,variation="rank",ylim=c(0,44),bar=FALSE,col=0)

#endgraph
LSD.test(model,"virus",p.adj="bon")