> On 26 Apr 2015, at 17:30 , Thierry Onkelinx wrote:
>
> Dear Mario,
>
> The interpretation is the same: the average at the reference situation
> which is the group that has f1 == "f1 level1" and f2 == "f2 level1".
A little more precisely: It is the estimate of the expected value at the
refer
The parameter is different because the model without intercept assumes that
effect of f1 is independent on the effect of f2. So you force f1b:f2ll to
be 0.
The interpretation is the same. The fit is conditional on the model
(interaction or no interaction).
ir. Thierry Onkelinx
Instituut voor natu
Dear Thierry,
That is the problem. I read that interpretation is the same, but the
Intercept value of summary is different:
The mean of level "a" of f1 and level "I" of f2 (first level of each
factor) is 0.7127851.
When I run model with interaction term:
summary.lm(aov(y~f1*f2,data=dt))
Coeff
Dear Mario,
The interpretation is the same: the average at the reference situation
which is the group that has f1 == "f1 level1" and f2 == "f2 level1".
Best regards,
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteits
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,
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