[R-sig-eco] GLS, GEE or LMM ??

Jens Oldeland oldeland at gmx.de
Fri Apr 16 12:49:57 CEST 2010


Dear All, 

I have run into a number of questions, and thus I hope you could help me 
out. I am modelling the effect of oyster density and nutrients on the 
bodyweight of mussels (population average).
Data was sampled at three different stations over 8 years, with values 
measured in springtime once per year.

I was following Zuur et al 2009 Mixed Effects Models (wonderful book!), 
but got lost at some points since different models lead to totally 
different results.

a) the first question is about "centring data". Zuur suggest to center 
parameters (p.334) if they are highly correlated with the intercept. 
When I apply a lme (family=gaussian, random ~ 1 | bank,  correlation = 
corAR1(form = ~ daycount)) I have to center nearly all the values. When 
I apply a GEE then there is no correlation at all (r=0.14).
Actually, centring the data leads to the same output at the end (for the 
lme)

b) Choosing GEE, the effect of one parameter (salinity) is highly 
significant, while using the LMM approach it is not, which would be 
better for our interpretation...
But why? Is it because GEE should not be used on normally distributed 
data? I know that GEE uses sandwich estimator and LMM uses ML. Which one 
would be more "trustworthy" or conservative?

c) one last qeustion: negative AICs, which one is better. AIC: -10 or -5 
? I have read contrasting statements. Is there any proof?? Does it hold 
for BIC as well?

thank you in advance!
Jens

-- 
+++++++++++++++++++++++++++++++++++++++++
Dipl.Biol. Jens Oldeland
Biodiversity of Plants
Biocentre Klein Flottbek and Botanical Garden
University of Hamburg 
Ohnhorststr. 18
22609 Hamburg,
Germany

Tel:    0049-(0)40-42816-407
Fax:    0049-(0)40-42816-543
Mail: 	Oldeland at botanik.uni-hamburg.de
        Oldeland at gmx.de 	(for attachments > 2mb!!)
Skype:	jens.oldeland
http://www.biologie.uni-hamburg.de/bzf/fbda005/fbda005.htm
+++++++++++++++++++++++++++++++++++++++++



More information about the R-sig-ecology mailing list