Re: [R] how calculation degrees freedom

From: Douglas Bates <dmbates_at_gmail.com>
Date: Sat 28 Jan 2006 - 10:52:45 EST

On 27 Jan 2006 23:08:28 +0100, Peter Dalgaard <p.dalgaard@biostat.ku.dk> wrote:
> Søren Højsgaard <Soren.Hojsgaard@agrsci.dk> writes:
>
> > Along similar lines, I've noticed that the anova() function for lmer
> > models now only reports the mean squares to go into the numerator
> > but "nothing for the denominator" of an F-statistic; probably in
> > recognition of the degree of freedom problem. It could be nice,
> > however, if anova() produced even an approximate anova table which
> > can be obtained from Wald tests. The anova function could then print
> > that "these p-values are large sample ones and hence only
> > approximate"...
>
> I'm reasonably convinced by now that the relevant denominator is
> always the residual variance, but it is happening via deep magic that
> I don't quite understand... (and is quite counterintuitive to people
> who are used to the traditional ANOVA decompositions in orthogonal
> designs)

Not deep magic for you, Peter. The slot called rXy in the fitted model is analogous to the first p components of the "effects" component in an lm model. Cut it up according to the terms and sum the squares.

> While we're on the subject: It would be desirable to have Wald tests
> for specific terms rather than the "Type 1" (sorry, Bill) progressive
> ANOVA table. Just like we already have in lme().

I think this is the point where I mention the Open Source nature of project. Sorry to say that it is not a priority for me right now.



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