Yes, that works fine too. It likely depends on what you want to show and to
whom. The audience might be ready to see the equivalence between t-tests and
anova(lm(...)) but not yet prepared for variance components.
- Peter
> On 27 Dec 2022, at 18:55 , Greg Snow <538...@gmail.com> wrote:
>
> Why
Why compute the differences manually when `aov` can do paired
comparisons on this data as is:
summary(aov(extra ~ factor(group) + Error(ID), data=sleep ))
gives the same F and P values
On Tue, Dec 27, 2022 at 3:32 AM Gabor Grothendieck
wrote:
>
> Good idea.
>
> On Mon, Dec 26, 2022 at 12:59 PM
Good idea.
On Mon, Dec 26, 2022 at 12:59 PM peter dalgaard wrote:
>
> My usual advice on getting nonstandard F tests out of anova() is to fit the
> models explicitly and compare.
>
> So how about this?
>
> fit1 <- lm(diff(extra,10) ~ 1, sleep)
> fit0 <- update(fit1, ~ -1)
> anova(fit0, fit1)
>
>
My usual advice on getting nonstandard F tests out of anova() is to fit the
models explicitly and compare.
So how about this?
fit1 <- lm(diff(extra,10) ~ 1, sleep)
fit0 <- update(fit1, ~ -1)
anova(fit0, fit1)
-pd
> On 26 Dec 2022, at 13:49 , Gabor Grothendieck wrote:
>
> Suppose we want to
