[R-sig-ME] degrees of freedom in mixed model

Baldwin, Jim -FS jbaldwin at fs.fed.us
Fri Jan 24 16:40:32 CET 2014


S Ellison:  Despite you being a chemist, I think you're at least mostly correct.  But from the construction of my statement, it's obvious that I am a statistician and I'm allowed, by law, to be wrong 5% of the time.  And if I claim to be a Frequentist, I don't even have to identify which of my particular statements are incorrect.

Jim

Jim Baldwin
Station Statistician
Pacific Southwest Research Station
USDA Forest Service

-----Original Message-----
From: r-sig-mixed-models-bounces at r-project.org [mailto:r-sig-mixed-models-bounces at r-project.org] On Behalf Of S Ellison
Sent: Friday, January 24, 2014 5:40 AM
To: Iain Gallagher; r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] degrees of freedom in mixed model


> library(lme4)
> model1 <- lmer(value~group + (1|animal), data=bip)
> summary(model1)
>
.......
> so I'd then have:
>
> qf(0.95,3,5) or qf(0.95,3,4)
>
> for my critical F value?
>
> Any advice (incuding whether the appraoch is right) would be useful.

It's the wrong approach.

You are using lmer, which uses maximum likelihood estimation, not classical sums of squares. The degrees of freedom don't mean the same thing, and the distribution of REML estimates of variance isn't necessarily chi-squared. So F is interpretable in the same way as it would be in classical anova.

If you want p-values from an lmer model, you could get hold of the lmerTest package. Other recommended approaches include variants on MCMC. There is a great deal of controversy on this point, though; try Googling "p-values from lmer" with particular attention to anything by Douglas Bates (the package author). You _should_ find enough to make you worry that the method used by lmerTest (which as I understand it implements a method used by SAS) comes with quite strong theoretical objections. I am quite sure the lmerTest authors know that perfectly well and offer lmerTest as a package for those who want to find out or for those whose management insist on a SAS-compatible answer. But if I read correctly, that doesn't make it the right thing to do

[Caveat - I'm a chemist. I could be wrong about this]

>
> Best
>
> iain
>
>       [[alternative HTML version deleted]]



*******************************************************************
This email and any attachments are confidential. Any use...{{dropped:17}}



More information about the R-sig-mixed-models mailing list