Two-factor ANOVA Help

On 10/8/05, Jim Brindle <j_brindle at hotmail.com> wrote:

Hello,

I am trying to perform a two-factor ANOVA analysis using a blocking design with "Vol" as the response variable.  My intent is to have "Rater" treated as the treatment variable and the "Pipe" treated as the blocking variable.  I am reading and preparing my dataset using the following three lines of code:

values <- read.table("filename", header=TRUE)
attach(values)
values = data.frame(values)

The dataset is the following:

Pipe Rater Volume
1    A       5.129
1    B       5.296
1    C       4.679
1    D       4.776
2    A       8.519
2    B       8.482
2    C       7.659
2    D       7.798
3    A       13.769
3    B       14.621
3    C       12.418
3    D       13.189

Below there are 2 versions which I've used to run my analysis.

Option #1:

g <- lm(Volume ~ factor(Rater) + factor(Pipe), values)
print(anova(g))

Option #2:

Rater <- as.factor(Rater)
Pipe <- as.factor(Pipe)
g <- lm(Volume ~ Rater + Pipe, values)
print(anova(g))


A couple of questions I have are:

1.  I thought that option #1 and option #2 would have given me the same results and they don't appear to.  The only difference (to me) is how I have specified the factors used in the model.  However, there appears to be something else I am missing and I was just wondering if anyone has any insight as to which is the correct way to code this analysis?

Note that values, as returned from read.table, is already a data frame
and Rater is already a factor so you only need to convert Pipe to a
factor:

values <- read.table("filename.dat", header = TRUE)

# shows classes of columns among other things
# note that Rater is already a factor and values is already a data frame
str(g)

# convert Pipe to a factor
values$Pipe <- factor(values$Pipe)
g <- lm(Volume ~., values)
g

2.  Unless otherwise specified is there a particular reference level that R uses by default - for example in this case, the second treatment level (Rater B)?

By default R uses treatment contrasts and uses the first level as the baseline.
You can change this using contrasts and contr.treatment.

 e.g. To use treatment effects on Pipe with level 2 as the baseline:

contrasts(values$Pipe) <- contr.treatment(3, base = 2)
g2 <- lm(Volume ~., values)
g2

3.  Is there a good reference someone can point me to for more insight on the two-factor ANOVA analysis with R?

See ?read.table, ?contrasts, ?contr.treatment