[R-sig-ME] compound symmetry correlation structure in nlme
Rian Dickson
rdd at sfu.ca
Thu Jun 16 21:32:49 CEST 2011
hello all,
I am analyzing some data with repeated measures on individuals, and want to test different correlation structures.
In Zuur et al (2007) they state "the inclusion of a random intercept in a GLM is imposing the compound symmetrical correlation structure, just as it did in the linear mixed model" (Chapter 13, p.323), which I understand as meaning that if a random intercept is included in a model, then the compound symmetry correlation structure is implied.
When I run the following two models (which are identical, except that in the second one I explicitly specify the correlation structure), I get the same estimates for the random and fixed effects, but the AIC and BIC values differ, because the second model has one more parameter (for the correlation structure).
global.ri.lme <- lme(Log.minH ~ site + f.year + cohort + emerg + emergSQ + pri + priSQ
+ start.t + startSQ + sea + tidem + tided, data = SUSCforage, random = ~1|scoterID,
method = "REML")
global.ri.cs1.lme <- lme(Log.minH ~ site + f.year + cohort + emerg + emergSQ + pri + priSQ
+ start.t + startSQ + sea + tidem + tided, data = SUSCforage, random = ~1|scoterID,
correlation = corCompSymm(form = ~1|scoterID), method = "REML")
So, if I want to obtain an accurate AIC value, which should I use?
thank you,
Rian
*************************************
Rian Dickson
M.Sc. candidate
Centre for Wildlife Ecology
Department of Biological Sciences
Simon Fraser University
8888 University Drive
Burnaby BC V5A 1S6
778.782.5618
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