Split-plot Design
Your question is not very clear, but if you are trying to match the
results in Kuehl, you need a fixed-effects model:
dat <- read.table("expl14-1.txt", header=TRUE)
dat$block <- factor(dat$block)
dat$nitro <- factor(dat$nitro)
dat$thatch <- factor(dat$thatch)
colnames(dat) <- c("block","nitro","thatch","chlor")
m1 <- aov(chlor~nitro*thatch+Error(block/nitro), data=dat)
summary(m1)
Mixed-effects models and degrees of freedom have been discussed many
times on this list....search the archives.
K Wright
On Thu, Mar 20, 2008 at 12:39 PM, <marcioestat at pop.com.br> wrote:
Hi listers,
I've been studying anova and at the book of Kuehl at the chapter
about split-plot there is a experiment with the results... I am trying to
understand the experiments and make the code in order to obtain the
results... But there is something that I didn't understand yet...
I have a split-plot design (2 blocks) with two facteurs, one
facteur has 4 treatments and the other facteur is a measure
taken in three years...
I organize my data set as:
Nitro Bloc Year Measure
a
x
1 3.8
a
x
2 3.9
a x 3 2.0
a y 1 3.7
a y 2
2.4
a y 3
1.2
b x
1 4.0
b x
2 2.5
and so on...
So, I am trying this code, because I want to test each factor and the
interaction...
lme=lme(measure ~ bloc + nitro + bloc*nitro, random= ~ 1|year,
data=lme)
summary(lme)
The results that I am obtaining are not correct, because
I calculated the degrees of fredom and they are not
correct... According to this design I will get two errors one for the
whole plot and other for the subplot....
Well, as I told you, I am still learning... Any suggestions...
Thanks in advance,
Ribeiro
[[alternative HTML version deleted]]
_______________________________________________ R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models