[R-sig-eco] "lack of fit" computation from LME model?

[Gavin Simpson]

Hi Laura,

You might want to look at the lmmfit package:

http://finzi.psych.upenn.edu/R/library/lmmfit/html/lmmfit-package.html

which has several such measures (well, goodness of fit) for models with
one grouping variable.

You might get more traction on the R Mixed Models SIG.

I often wonder (knowing nothing about this particular topic) about the
merit of "test". Surely if the linearity assumption of the model you
fitted is not appropriate, this will show up in the model residuals as
patterns/curves. This would be part of a standard model evaluation
anyway.

HTH

G

On Tue, 2011-09-27 at 14:06 +0000, L Quinn wrote:
> Dear list,
> I recently submitted a paper in which I analyzed plant growth response to several environmental factors in several sites. I wanted to account for the variation attributable to the different sites, so I made "site" a random effect in a simple LME regression model (e.g. m<-lme(plantgrowth~nitrogen,random=~1|site,method="ML"); library nlme). I had 10 observations in each of 11 sites. Seemed fairly straightforward to me.
> When reviews came back, one reviewer and the editor requested that I compute a "lack of fit" term for my regressions without which they couldn't be confident that linear models were most appropriate for my data. I have not done this before, and I have not seen anything about this for LME models when I have searched. I have only seen it for regular regression tests, but I don't think I can apply what I would find in regular regression tests to this LME model because I would lose the random effect. I know about model checking via diagnostic plots, etc, but I don't think this is what they want. They seem to want me to generate an F statistic and a p value for this "lack of fit" term. 
> My questions are: 
> 1.) is this even possible/practical within a LME model? 
> 2.) if so, what steps should I take to complete this task?3.) if not, can you suggest other diagnostics that might satisfy what they're looking for?
> I have a feeling this is a fairly elementary question/procedure, so I hope I am not wasting anyone's time. Please help if you can. I am happy to provide any more information that may be needed.
> Thank you in advance.
> Lauren Quinn
> 
> 
> 
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