Re: [R] Linear Trend in Residiuals From lme

From: Douglas Bates <bates_at_stat.wisc.edu>
Date: Thu 10 Aug 2006 - 07:43:32 EST

On 8/9/06, Rick Bilonick <rab45+@pitt.edu> wrote:
> On Wed, 2006-08-09 at 15:04 -0500, Douglas Bates wrote:
> > On 8/9/06, Rick Bilonick <rab45+@pitt.edu> wrote:
> > > I'm fitting a mixed effects model:
> > >
> > > fit.1 <- lme(y~x,random=~1|id,data=df)
> > >
> > > There are two different observations for each id for both x and y. When
> > > I use plot(fit.1), there is a strong increasing linear trend in the
> > > residuals versus the fitted values (with no outliers). This also happens
> > > if I use random=~x|id. Am I specifying something incorrectly?
> >
> > Could you provide a reproducible example please?
> >
> > I suspect that the problem comes from having only two observations per
> > level of id. When you have very few observations per group the roles
> > of the random effect and the per-observation noise term in explaining
> > the variation become confounded. However, I can't check if this is
> > the case without looking at some data and model fits.
>
> I tried using geeglm from geepack to fit a marginal model. I understand
> this is not the same as a mixed effects model but the residuals don't
> have the linear trend. Should I avoid using lme in this case?

Probably.



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