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model comparison in glmmADMB

2 messages · RH Gibson, School Biological Sciences, Ben Bolker

Original
RH Gibson, School Biological Sciences
# 
I am trying to compare two models to see whether the random effect is 
significant, using the anova command I get the following output:
Analysis of Variance Table

Model 1: xx ~ nsn * Insect.type + ara * Insect.type + 
offset(logTotal.grains)
Model 2: xx ~ nsn * Insect.type + ara * Insect.type + 
offset(logTotal.grains)
  NoPar  LogLik Df -2logQ P.value
1    12 -2427.4
2    11 -2427.9 -1  -0.96
Warning message:
In pchisq(q, df, lower.tail, log.p) : NaNs produced

Why might this be happening? Can I still use the log likelihood ratio as a 
comparison method? And more generally is this an appropriate test of the 
random effect?

The full models are as follows:
m7<-glmmadmb(x~nsn*Insect.type+ara*Insect.type+offset(logTotal.grains)+(1|Site),data=data1, 
zeroInflation=TRUE, family="nbinom")
zeroInflation=TRUE, family="nbinom")



----------------------
RH Gibson, School Biological Sciences
Rachel.Gibson at bristol.ac.uk
Ben Bolker
# 
RH Gibson, School Biological Sciences <Rachel.Gibson at ...> writes:
[snip]
anova.glmmadmb is not smart enough to put the terms in order of
increasing complexity, and it expects you to do so.  This will be
clarified/fixed in the next version.

  More generally, LRTs of random effects are OK but not great; they are
known to be conservative (see http://glmm.wikidot.com/faq both for ways
to test random effects and for questions as to why you would be wanting
to test the significance of a random effect in the first place).