Dear R users,
This is probably a very stupid question, nevertheless I obviously am not
qualified enough
to cope with it. I do not understand what the coefficients are that are output
by running
summary.lm on an aov object. I thought they should be the differential effects
for the levels of the factor and the overall mean, but they are obviously not,
as illustrated by the following simple example:
x <- c(1:15); y <- factor(c(rep("a", 5), rep("b", 10)))
> tapply(X=x, INDEX=y, FUN=mean)
a b
3.0 10.5
> mean(x)
[1] 8
> a <- aov(x ~ y)
> summary.lm(a)$coef
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.0 1.192928 2.514821 0.0258555905
yb 7.5 1.461032 5.133357 0.0001921826
> model.tables(a)
Tables of effects
y
a b
-5 2.5
rep 5 10.0
Besides, I fit a factor with two levels, "a" and "b", but there is only the
"yb" coefficient for the "b" level, no "ya" coefficient for the "a" factor
level. I read a lot of materials on anova with R, but I could not find what are
these coefficients. I would be grateful if someone gives me some clue. And what
is the intercept term? I though it should be the overall mean, but it is
obviously not.
Regards and best wishes,
Martin Ivanov
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