# Milliken and Johnson Example 13.1
empty <- read.table("empty.dat",header=T)
empty$A <- factor(empty$A)
empty$B <- factor(empty$B)

# full model for unbalanced data
empty.aov <- aov(y~A*B, empty)
# Type I SS
print(summary(empty.aov))
# Type III SS
print(drop1(empty.aov,formula(empty.aov)))
# no easy way to do Type IV SS

#balanced subsets
empty1 <- empty[empty$A != 1 & empty$B != 3,]
print(empty1)
empty1.aov <- aov(y~A+B, empty1)
print(drop1(empty1.aov,formula(empty1.aov)))
empty2 <- empty[empty$A != 3 & empty$B != 2,]
print(empty2)
empty2.aov <- aov(y~A*B, empty2)
print(drop1(empty2.aov,formula(empty2.aov)))
empty3 <- empty[empty$B == 1,]
print(empty3)
empty3.aov <- aov(y~B, empty3)
print(summary(empty3.aov))

# least squares means
library(pda)
print(lsmean(empty.aov))