## April 12, 2007 550.413 Section

### More on the popcorn data ###

# Prepping the data
popcorn = read.table("/Users/Elizabeth/Documents/popcorn.txt", header=T)
attach(popcorn)
names(popcorn)
#Make sure all factors are treated as categorical variables.
PopcornBrand=as.factor(PopcornBrand)
Power = as.factor(Power)
OvenBrand = as.factor(OvenBrand)
PoppingTime = as.factor(PoppingTime)

# Create new variable which indicates which treatment an observation is in.
Treatment = as.factor(paste(PopcornBrand, OvenBrand, sep=""))
# note: this new variable allows us to turn a multi-way ANOVA into one-way cell means ANOVA

popcorn=data.frame(popcorn, Treatment)
popcorn

## Model 1 ##
PopMod1 = aov(PctEdible ~ PopcornBrand*OvenBrand)
anova(PopMod1)

set1 = c("PopcornBrand", "OvenBrand")

TukeyHSD(PopMod1, set1, conf.level = .9)
#visualize plots and where estimate falls in relation to 0
par(mfcol=c(1,2))
plot(TukeyHSD(PopMod1, set1, conf.level = .9))

# All pairwise comparisons within treatments
# ordered = T gives all positive estimates.
TukeyHSD(PopMod1, "PopcornBrand:OvenBrand", conf.level = .9, ordered = T)

# The default is all factors
TukeyHSD(PopMod1, conf.level = .9)

## Model 2 ##

PopMod2 = aov(PctEdible ~ Treatment)
anova(PopMod2)
TukeyHSD(PopMod2, conf.level = .9)

detach(popcorn)

### Looking at the mouse data ###

mouse = read.table("/Users/Elizabeth/Documents/mousegrowth.txt", header = T,sep=",")
Hormone = as.factor(Hormone)
Diet = as.factor(Diet)
Treatment = as.factor(Treatment)

attach(mouse)
names(mouse)

m1 = aov(Weight.Gain ~ Hormone*Diet)
m2 = aov(Weight.Gain ~ Treatment)

#The following 2 give the same thing
TukeyHSD(m1, conf.level = .9)
TukeyHSD(m2, conf.level = .9)
#orders the factors level differences so they are all positive.
TukeyHSD(m2, conf.level = .9, ordered = T)

## using scheffe.R
# Note: only for one-way ANOVA!!

#register function
source("/Users/Elizabeth/Documents/scheffe.R")

#all pairwise comparisons
scheffe(m2,"allpairs",.95)

#define matrix using c(), number of rows = 6 = num treatment levels, num columns = 4 = num contrasts defined
contmatrix = matrix(c(1,0,0,-1,0,0, -1/3,-1/3,-1/3,1/3,1/3,1/3, 0,0,0,1,-.5,-.5, -1,0,0,0,0,1), 6,4)
contmatrix

#contrasts
scheffe(m2,contmatrix,.95)

detach(mouse)