Hi all,
I am doing anova multi factor and I found different Intercept when model
has interaction term.
I have the follow data:
set.seed(42)
dt <- data.frame(f1=c(rep("a",5),rep("b",5)),
f2=rep(c("I","II"),5),
y=rnorm(10))
When I run
summary.lm(aov(y ~ f1 * f2, data = dt))
The Intercept term is the mean of first level of f1 and f2. I can confirm
that with:
tapply(dt$y, list(dt$f1, dt$f2), mean)
I know that others terms are difference of levels with Intercept.
But I do not know what is Intercept when the model do not have interaction
term:
summary.lm(aov(y ~f1 + f2, data = dt))
I know that I can create a specific contrast table, by I would like
understand the default R output.
I read contrast sub-chapter on Crawley 2012 (The R book) and in his example
the Intercept is different when model has or not interaction term, but he
explain that Intercept is mean of first level of the factors.
Best regards,
Mario
.............................................................
Mario José Marques-Azevedo
Ph.D. Candidate in Ecology
Dept. Plant Biology, Institute of Biology
University of Campinas - UNICAMP
Campinas, São Paulo, Brazil
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