[R-sig-ME] Poisson mixed models
Renwick, A. R.
a.renwick at abdn.ac.uk
Tue Oct 21 12:24:38 CEST 2008
I did run a GLMM with poisson - that is the model type I want to use. I only used a GLMM with quasipoisson to check the scale parameter as I am unaware as to how to check if you have over/under dispersion in the poisson model, and hence violating the assumption of the model, and other way.
# glmm with poisson family
mix<-lmer(trianlarvae~Sex+width+sess+Nhat+Sex:width+Sex:sess+Sex:Nhat+width:sess+width:Nhat+sess:Nhat+(1|LocTran), family=poisson, data=larv, REML=FALSE)
Generalized linear mixed model fit by the Laplace approximation
Formula: trianlarvae ~ Sex + width + sess + Nhat + Sex:width + Sex:sess + Sex:Nhat + width:sess + width:Nhat + sess:Nhat + (1 | LocTran)
AIC BIC logLik deviance
464 572.7 -212 424
Groups Name Variance Std.Dev.
LocTran (Intercept) 1.3462 1.1603
Number of obs: 1697, groups: LocTran, 14
Estimate Std. Error z value Pr(>|z|)
(Intercept) -4.218e+00 1.708e+00 -2.4694 0.0135 *
Sexmale 6.999e-01 1.189e+00 0.5887 0.5561
width -1.426e-01 2.360e-01 -0.6044 0.5456
sessAugust 1.486e+00 2.060e+00 0.7212 0.4708
sessJune -1.545e+01 1.212e+03 -0.0127 0.9898
sessOctober 3.119e+00 1.838e+00 1.6973 0.0896 .
Nhat -4.909e-02 5.814e-02 -0.8442 0.3985
Sexmale:width 1.159e-01 7.612e-02 1.5222 0.1280
Sexmale:sessAugust -7.540e-01 1.632e+00 -0.4621 0.6440
Sexmale:sessJune 1.310e+01 1.212e+03 0.0108 0.9914
Sexmale:sessOctober -1.118e+00 1.223e+00 -0.9139 0.3608
Sexmale:Nhat 9.881e-03 1.012e-02 0.9765 0.3288
width:sessAugust 8.245e-01 5.882e-01 1.4017 0.1610
width:sessJune -4.034e-02 2.791e-01 -0.1445 0.8851
width:sessOctober -1.045e-02 2.057e-01 -0.0508 0.9595
width:Nhat 4.239e-03 3.654e-03 1.1600 0.2460
sessAugust:Nhat -1.484e-01 1.299e-01 -1.1422 0.2534
sessJune:Nhat 2.646e-02 6.249e-02 0.4235 0.6719
sessOctober:Nhat 1.462e-03 5.776e-02 0.0253 0.9798
From: Martin Henry H. Stevens [mailto:HStevens at muohio.edu]
Sent: 21 October 2008 11:19
To: Renwick, A. R.
Cc: r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] Poisson mixed models
So you tried a GLMM with quasipoisson and a GLM with Poisson? How about a GLMM with Poisson? Sounds like you may have a random effect that is necessary for your hypothesis test, but which does not explain any variation (but I really have no way of knowing).
On Oct 21, 2008, at 5:33 AM, Renwick, A. R. wrote:
> Dear All
> There has been a lot of talk recently on this forum regarding (over)
> dispersion and quasi models. I am running a GLMM with a poisson
> family for some tick burden data I have and I wanted to check if I had
> overdispersion in my model (and thus a poisson family would be
> inappropriate). The only method I have found to do this is to run the
> model with a quasipoisson family and then ask for the scale parameter
> However, when I do this my model appears severely UNDER dispersed:
> Without the random effect in the model (i.e a GLM) the scale parameter
> is 1.07 - almost perfect for a poisson family. Is the method I am
> trying not appropriate to determine the dispersion in the mixed model?
> Does anyone know a better method?
> Many thanks,
> The University of Aberdeen is a charity registered in Scotland, No
> R-sig-mixed-models at r-project.org mailing list
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