[R-sig-ME] Lmer with family = quasipoisson

[Renwick, A. R.]

I was wondering if anybody could explain why an AIC can be calucluated for a lmer model with a quasi poisson distriution and not a glm.
I have also found that the AIC's are extremely sensitive in the lmer model, for example removing a term with very low t-values resulted in an increase in AIC of 284.
Many thanks,
Anna

MODEL1:

mix<-lmer(realdis~sex+width+sess+sex:width+sex:sess+sess:width+(1|site),family=quasipoisson,data=move,subset=-52)
> summary(mix)
Generalized linear mixed model fit by the Laplace approximation
Formula: realdis ~ sex + width + sess + sex:width + sex:sess + sess:width +      (1 | site)
   Data: move
 Subset: -52
   AIC   BIC logLik deviance
 11019 11117  -5490    10979
Random effects:
 Groups   Name        Variance Std.Dev.
 site     (Intercept)  9.1673  3.0278
 Residual             76.4532  8.7438
Number of obs: 976, groups: site, 14

Fixed effects:
             Estimate Std. Error t value
(Intercept)   2.76589    0.91021  3.0387
sexm          0.17425    0.41856  0.4163
widthn        0.26750    0.99495  0.2689
widthw       -0.47361    0.55549 -0.8526
sess2        -0.43403    0.64479 -0.6731
sess3        -0.16228    0.85141 -0.1906
sess4        -0.40075    0.63427 -0.6318
sexm:widthn   0.78322    0.63070  1.2418
sexm:widthw   0.39836    0.44387  0.8975
sexm:sess2    0.02061    0.51386  0.0401
sexm:sess3    0.17900    0.52713  0.3396
sexm:sess4    0.36188    0.53644  0.6746
widthn:sess2  0.53589    0.83917  0.6386
widthw:sess2 -0.11500    0.65798 -0.1748
widthn:sess3 -0.19799    1.03927 -0.1905
widthw:sess3 -0.99033    0.86773 -1.1413
widthn:sess4 -0.17498    0.94033 -0.1861
widthw:sess4 -1.03199    0.75236 -1.3717

REMOVE WIDTH:SESS INTERACTION
 mix1<-lmer(realdis~sex+width+sess+sex:width+sex:sess+(1|site),family=quasipoisson,data=move,subset=-52)
> summary(mix1)
Generalized linear mixed model fit by the Laplace approximation
Formula: realdis ~ sex + width + sess + sex:width + sex:sess + (1 | site)
   Data: move
 Subset: -52
   AIC   BIC logLik deviance
 11303 11372  -5638    11275
Random effects:
 Groups   Name        Variance Std.Dev.
 site     (Intercept)  6.8207  2.6117
 Residual             84.5884  9.1972
Number of obs: 976, groups: site, 14

Fixed effects:
            Estimate Std. Error t value
(Intercept)   3.0503     0.7807   3.907
sexm          0.1780     0.4249   0.419
widthn        0.1302     0.7417   0.176
widthw       -0.7784     0.5217  -1.492
sess2        -0.4633     0.4770  -0.971
sess3        -0.9002     0.4859  -1.853
sess4        -0.9513     0.4733  -2.010
sexm:widthn   0.7431     0.6553   1.134
sexm:widthw   0.3856     0.4592   0.840
sexm:sess2    0.0963     0.5314   0.181
sexm:sess3    0.2302     0.5511   0.418
sexm:sess4    0.3524     0.5481   0.643

Change in AIC =  11303 - 11019 = an increase of 284


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