wbw <- read.table("http://www.stat.ufl.edu/~winner/data/whole_breast_weight.dat",
header=F,col.names=c("trt","repnum","base","meth","wtg"))
attach(wbw); names(wbw)

# Treatment Ordering: BS, BSM, BC, BCM

trt.f <- factor(trt)

require(multcomp)

wbw.mod1 <- aov(wtg ~ trt.f)
summary(wbw.mod1)

wbw.glht <- glht(wbw.mod1, linfct = mcp(trt.f="Tukey"))
summary(wbw.glht) # the summary of the tests
confint(wbw.glht)

windows(width=5,height=3,pointsize=10)
plot(wbw.glht)
title(sub="Whole Breast Weight Data",adj=0)
mtext("Tukey Honest Significant Differences",side=3,line=0.5)

### Creating three orthogonal contrasts, testing each
contr.ort1 <- rbind(
"Corn - Sorghum"=c(-1,-1,1,1),"Meth - NoMeth"=c(-1,1,-1,1),
"(C-S)M - (C-S)NM"=c(1,-1,-1,1))

confint(glht(wbw.mod1,linfct=mcp(trt.f=contr.ort1)))

### Treating "BC" as a Control Treatment - Dunnett's Test

levels(trt.f)
trt.f1 <- relevel(trt.f, ref="3")
levels(trt.f1)

wbw.mod2 <- aov(wtg ~ trt.f1)
summary(wbw.mod2)


wbw.Dunnett <- glht(wbw.mod2, linfct=mcp(trt.f1="Dunnett"))
summary(wbw.Dunnett)
confint(wbw.Dunnett)



windows(width=5,height=3,pointsize=10)
plot(wbw.Dunnett,sub="Whole Breast Weight Data")
mtext("Dunnet's Method",side=3,line=0.5)

### Duncan's and SNK Test

require(agricolae)

duncan.test(wbw.mod1,"trt.f",main="Whole Breast Weight",console=TRUE)
SNK.test(wbw.mod1,"trt.f",main="Whole Breast Weight",console=TRUE)