karate <- read.csv("http://www.stat.ufl.edu/~winner/data/karate_board.csv",
           header=T)

attach(karate)
names(karate)

kb.mod1 <- lm(Deflect ~ X1 + X2 + X3 + X4 + X1X4 + X2X4 + X3X4)
anova(kb.mod1)

kb.mod2 <- lm(Deflect ~ X1 + X2 + X3 + X4)
anova(kb.mod2)

anova(kb.mod2, kb.mod1)

### As the interaction, is highly non-significant, Use Model 2 for
###    main effects tests

kb.mod3 <- lm(Deflect ~  X4)
anova(kb.mod3)

kb.mod4 <- lm(Deflect ~ X1 + X2 + X3)
anova(kb.mod4)

anova(kb.mod3,kb.mod2)
anova(kb.mod4,kb.mod2)

kb.mod5 <- aov(Deflect ~ factor(Wood) + factor(Bdtype))
anova(kb.mod5)
drop1(kb.mod5)
TukeyHSD(kb.mod5)

options(contrasts=c("contr.sum","contr.poly"))

kb.mod6 <- aov(Deflect ~ factor(Wood)*factor(Bdtype))
anova(kb.mod6)

# library(car)
# Anova(kb.mod6,type="III")