[R-sig-ME] Variance explained by random factor

Ken Beath ken at kjbeath.com.au
Thu Aug 14 11:10:10 CEST 2008

On 14/08/2008, at 1:17 AM, Renwick, A. R. wrote:

> I am currently trying to run a lmer model with poisson  
> distrubution.  I tested the model with a model without the random  
> effect and it inferred that I should include the random effect:
> ma1<-glm(RoundedOverlap~sess+breedfem,family=poisson,data=Male)
> mixed<-lmer(RoundedOverlap~sess+breedfem+sess:breedfem+(1| 
> Site),family=poisson,data=Male)
> #test to see if sig difference between glm and glmm
> as.numeric(2*(logLik(mixed)-logLik(ma)))
> #99.16136
> pchisq(99.16136,1,lower=FALSE)
> #2.327441e-23  so should use a GLMM

The problem may be due to the random effects model containing an  
interaction term sess:breedfem that the glm doesn't.


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