[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)
   Data: larv
 AIC   BIC logLik deviance
 464 572.7   -212      424
Random effects:
 Groups  Name        Variance Std.Dev.
 LocTran (Intercept) 1.3462   1.1603
Number of obs: 1697, groups: LocTran, 14

Fixed effects:
                      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

-----Original Message-----
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

Hi Anna,
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
> using:
> lme4:::sigma(model)
> However, when I do this my model appears severely UNDER dispersed:
>  sigmaML
> 3.779694e-06
> 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,
> Anna
> The University of Aberdeen is a charity registered in Scotland, No
> SC013683.
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> R-sig-mixed-models at r-project.org mailing list
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